So many recalls, so little research: a review of the literature and road map for future research.
Welcome to the Decade of the Recall ... major crises overtook the spinach, toy, and pet food industries ... [there is a] seemingly interminable progression of one recall after another on a regular basis.--Forbes (Levick, 2011).
The operational and financial impacts of disruptions to today's complex global supply chains are one of the most pressing concerns for supply chain managers (Blackhurst, Dunn & Craighead, 2011). One especially damaging and increasingly frequent type of disruption occurs when tainted products are discovered and need to be removed from circulation--this process is formally known as a product recall (1) (Roth, Tsay, Pullman & Gray, 2008). The consequences of product recalls can be considerable. In a recent survey, 81 percent of participating firms deemed the financial risk of recalls as "significant" to "catastrophic" (GMA, 2011). However, the financial repercussions of product recalls pale in comparison with the life-threatening risk tainted or defective products pose to consumers. The defective cars recently recalled by General Motors (GM), for example, resulted in 13 consumer deaths and roughly 31 crashes (Macdonald, Lynch & Burden, 2014). Given the profound impacts of product recalls, it is important that we, as a field, improve our understanding of these potentially devastating events.
Although past scholarship on product recalls is informative, our understanding of these events remains fragmented. As such, the objective of this research is to examine the state of product recall-related research and provide a road map for future research. Our research offers important implications for both managers and academics alike. For managers, we highlight insights related to four key aspects of recalls: (1) recall precursors (i.e., factors that may lead to recalls); (2) the recall process; (3) the impact of recalls; and (4) mitigation approaches (i.e., mechanisms firms can employ to reduce the impact of recalls). For scholars, we identify important research opportunities in the same four areas to promote and guide future research in this area.
ENGAGING INDUSTRY EXPERTS AND REVIEWING THE LITERATURE
For this research, we followed a two-step process. First, we leveraged insights from industry. Specifically, we drew on the expertise of executives along the entire supply chain--from source to consumer--which provided a unique and rare insight into product recalls. We gained initial access to executives through a supply chain center at a major university. From there, we asked participants to put us in contact with other employees from their firm or in other firms who would provide valuable insights into product recalls. In total, we conducted 55 interviews with executives from several different entities including suppliers, manufacturers, distribution centers/retail locations, nonprofit organizations focused on product safety, logistics providers, federal governmental agencies responsible for overseeing product recalls, and various subject matter experts. We also captured key insights from several focus groups composed of supply chain managers responsible for participating in some aspect of their company's product recall process. Together, the interviews and focus groups included participants representing a diverse set of industries (e.g., food, pharmaceutical, consumer product, and medical device) and job titles including Senior Director of Customer Service and Logistics, Director of Supply Chain Strategy, Recall Coordinator, Vice President of Quality Assurance, Foodborne Illness Investigator, and Vice President of Distribution. The primary objective of the interviews and focus groups was not to conduct a rigorous scientific investigation. Instead, the objective was to gain less formal, but still important, background insights about product recalls.
Next, we synthesized the extant product recall literature to identify potentially important gaps in our understanding. We identified relevant articles by conducting a keyword search for "product recall," "product recalls," "recall," "recalls," and "traceability" (2) in top supply chain, operations management, and logistics journals, management journals, and marketing journals (3) (see Appendix A for a complete list of journals). This process revealed 34 relevant articles (see Appendix SI for a summary of the articles and Appendix S2 for an itemized listing of the propositions or hypotheses in the articles). Two researchers independently coded the articles based on (1) focus (e.g., precursor, process, impact, or mitigation approach); (2) unit of analysis (e.g., firm, dyad, or network); and (3) methodology (e.g., empirical, (4) modeling, descriptive, or conceptual). The process began by randomly selecting and coding ten articles; following this, we discussed discrepancies and repeated the process until all the articles were coded (5) (see Table 1).
By oscillating between findings in the literature and insights from the interviews and focus groups, we were able to identify important research opportunities for supply chain management (SCM) scholars. This process also allowed us to identify several valuable, but underutilized theories in SCM research that can help guide future research on product recalls. In the sections that follow, we discuss the literature on the four main aspects of product recalls--precursors, processes, impacts, and mitigation approaches--identify research opportunities in each of the areas and suggest promising underutilized theories that can help guide future research.
PRODUCT RECALL PRECURSORS
Product recall precursors is an emergent topic in SCM that extends past scholarship in several related areas including process compliance (e.g., Laufer & Jung, 2010), statistical process control (e.g., Rungtusanatham, Anderson & Dooley, 1997), total quality management (e.g., Powell, 1995), and corporate risk aversion (e.g., Baysinger & Hoskisson, 1989). Research in the first three areas focus solely on product quality while the last area centers on avoiding general liabilities or dangers that may or may not lead to product quality failures. As such, research on product recall precursors is broader than the first three as it considers all factors that could lead to a quality failure yet narrower than the last.
Roughly half of the articles (44.1 percent or 15 articles) focused on recall precursors or factors that cause firms to have a higher (or lower) probability of experiencing product recalls (see Table 1 and Appendix SI). For example, Kiani, Shirouyehzad, Khoshsaligheh Bafti and Fouladgar (2009) highlight the value of investing in preventive and appraisal systems while others have examined operational issues that lead to product recalls, such as sourcing strategies (Li, Wang & Liu, 2011; Steven, Dong & Corsi, 2014), supplier selection (Das, 2011; Tse & Tan, 2011), buyer-supplier relationships (Chao, Iravani & Savaskan, 2009), ISO 9001 processes (Chiarini, 2015), and traceability issues (Alfaro & Rabade, 2009; Epelbaum & Martinez, 2014; Tse & Tan, 2012). Scholars have found, for instance, that when traceability is integrated with operational processes (Wang, Li & O'Brien, 2009) and production planning (Wang, Li, O'Brien & Li, 2010), firms can improve their products' overall quality and thus reduce the probability of experiencing product recalls.
There is also a growing amount of research on non-operational recall precursors. Bromiley and Marcus (1989) found decreases in shareholder value to be an insufficient deterrent of behavior that may lead to recalls, and that in some cases, it was actually profitable to produce unsafe products. More recently, Wowak, Mannor and Wowak (2015) investigated how Chief Executive Officer (CEO) compensation (stock option pay versus base pay) impacts the likelihood of a firm experiencing a product recall; they found that higher stock option pay promotes a lack of CEO caution and results in a higher probability of product safety issues. While these efforts represent important strides in our understanding of product recall precursors, significant opportunities remain for future researchers. Table 2 presents an overview of the future research opportunities. We discuss these research opportunities in the sections which follow.
Research Opportunity #1: Top Management Teams
Although scholars have examined operational and nonoperational recall precursors, the majority of research has centered on the former (see Appendix S1). As such, our understanding of the latter, such as how the composition and/or background of a firm's top management team (TMT) can impact the likelihood of product recalls, is scant. Strategy scholars have long suggested that a firm's strategic choices and level of performance is partially determined by the background characteristics of the firm's top executives (Hambrick & Mason, 1984). Consequently, if we examine a firm's TMT, we may discover new insights about why certain firms continuously struggle with product recalls while others go long periods without quality failures. We are not suggesting that scholars completely abandon examining operational issues, but rather expand the scope of their research to consider the role of top executives as well. This area of research is vastly underdeveloped, and thus, there are numerous research opportunities for scholars.
CEO Background. What we have done in the past--positions held and personal and professional experiences--shapes who we are and influences the decisions we make (e.g., Daily, Certo & Dalton, 2000; Guthrie & Datta, 1997). Little is known, however, about if or how a CEO's background impacts the probability of their firm's experiencing product recalls. For example, does a firm with a CEO who has an operations background experience fewer product recalls than firms with a CEO who has an accounting or marketing background? In the same vein as Wowak, Mannor and Wowak (2015), scholars could examine the relationship between CEO characteristics, such as personal risk-taking (Cain & McKeon, in press), hubris (Li & Tang, 2010), or self-confidence (Wowak & Hambrick, 2010), and the likelihood of their firms experiencing product recalls. For example, do firms with overconfident CEOs experience more recalls than firms with more modest CEOs?
TMT Composition. We also believe the composition of the TMT may impact the probability of firms experiencing product recalls (Hendricks, Hora & Singhal, in press). For example, do firms with a Chief Supply Chain Officer (CSCO (6)) experience fewer recalls than firms without a CSCO? CEOs are often tasked with increasing the firm's margins and profitability, which is typically accomplished by the proverbial cost-cutting across functions. This approach, however, can negatively impact product quality as firms may cut internal costs (e.g., product testing) too drastically. CSCOs can help reduce costs via strategic sourcing or other means while still maintaining product quality and thus firms with a CSCO may be less likely to experience quality failures.
Promising Underutilized Theory. Upper echelons theory (Hambrick & Mason, 1984) rests on two key tenets: "(1) executives act on the basis of their personalized interpretations of the strategic situations they face, and (2) these personalized construals are a function of the executives' experiences, values, and personalities" (Hambrick, 2007: 334) (see Table 3). In other words, executives interpret environmental cues through their own personalized lenses, which in turn influence how their firms respond to those cues (Hambrick & Mason, 1984). However, due to bounded rationality executives are unable to process all available information so they rely on their underlying cognitive bases and values to help them make decisions (Carpenter, Geletkanycz & Sanders, 2004).
Past scholarship examining upper echelons theory often uses the physical characteristics of the TMT, such as age, ethnicity, gender, tenure, education, and functional backgrounds, as proxies for psychological constructs that influence the way top executives process information and how they respond to that information (Connelly, Ketchen & Slater, 2011). Upper echelons theory sheds light on "why organizations do the things they do" and thus is particularly well-suited to examine why some firms experience product recalls more frequently than others (Hambrick, 2007: 334). By examining the biases of a firm's most influential actors--the top executives--we can gain rich insights into how likely firms are to experience product recalls and the underlying reasons why.
PRODUCT RECALL PROCESS
Research on the product recall process is similar, yet distinct from previous research on how firms recover from supply chain disruptions in general, such as natural disasters and strikes. Natural disasters (e.g., floods, tsunamis, earthquakes) are events that occur in a firm's external environment and thus lie outside a firm's control, whereas product recalls may be the result of a firm's actions or failure of internal processes and thus fall within a firm's control. Similarly, natural disasters center on regaining operational capability while product recall processes focus on extracting bad products from circulation; thus findings on supply chain disruptions in general may not transcend to the product recall process.
Although the product recall process is the lynchpin to success when tainted products are discovered and need to be removed from the chain, research in this area is scant (see Table 1 and Appendix SI). Only 7 articles (20.6 percent) focused on this aspect of product recalls. As such, the recall process is still considered a "black box" that has yet to be opened. Yaros and Wood (1979) were the first to attempt to open the "black box" by describing recall procedures developed by firms in the drug and cosmetic industry. Ketchen, Wowak and Craighead (2014) build upon their work by conducting a more in-depth investigation centered on how a firm's resource endowments and resource orchestration capabilities impact the recall process. Ketchen et al. (2014) identified four different types of product recalls firms experience and thus discovered that firms should not manage the product recall process with a "one size fits all" approach.
Hora, Bapuji and Roth (2011) also investigate the recall process, but focus primarily on the temporal aspect. Hora et al. (2011) discovered several factors, such as position in the chain and source of defect (e.g., design flaw versus manufacturing issue), that impact how long it takes firms to recall products. Scholars have also examined different recall strategies (e.g., proactive versus reactive) (Chen, Ganesan & Liu, 2009) and how Six Sigma principles can facilitate a firm's response to product recalls (Kumar & Schmitz, 2011). While scholars have captured key insights about the recall process (see Appendix SI), several important underdeveloped research areas remain for scholars to explore (see Table 2 for additional research opportunities).
Research Opportunity #2; Strategic Recall Process
The literature on strategic processes is often partitioned into two overarching areas (Huff & Reger, 1987): (1) strategy formulation (i.e., how decisions are generated); and (2) strategy implementation (i.e., how decisions are put into action). We adopted a similar approach and identified a research opportunity for both overarching areas. The research opportunity for strategy formulation centers on organizational culture, which influences how decisions are generated for the product recall process. Scholars could also consider the impact organizational culture has on the likelihood of firms experiencing product recalls and thus could be considered a boundary spanning factor as it may shed light on multiple aspects of product recalls. The research opportunity for strategy implementation focuses on supply chain complexity, which impacts the implementation of the product recall process. Both aspects individually as well as collectively influence a firm's product recall process, but do so in varying ways.
Organizational Culture. A firm's culture permeates the entire organization and thus influences a number of different factors, such as the degree of risk-taking and competitiveness (Deshpande, Farley & Webster, 1993). Intuitively, culture should be an important consideration when examining how firms respond to product recalls, but it has not been examined from a research perspective, which is somewhat surprising. Examining if and how organizational culture influences a firm's recall process or time to recall (e.g., Hora et al., 2011), and the effectiveness of a firm's recall efforts could reveal fascinating new insights.
One classification of organizational culture is based on the two dimensions of flexibility-control and internal-external (e.g., McDermott & Stock, 1999). Firms that have a flexible, internally focused culture tend to be characterized by a sense of family, commitment, and morale. As such, these firms may be more likely to implement a proactive and comprehensive recall process because they are less focused on cost and more focused on protecting consumers. Conversely, firms that have a controlled, externally focused culture tend to be characterized by productivity, goal achievement, competitiveness, and profitability, which may result in them implementing a reactive and less complete recall process because their focus is on minimizing costs.
Family-owned companies, such as Johnson and Johnson (J&J) (Eichenberger, 2011), often have organizational cultures that are flexible and internally focused, which we conjecture may influence how they respond to recalls. Consider how J&J handled the famous Tylenol recall in 1982, for example. J&J executed an extremely proactive and comprehensive recall; they cleared all Tylenol products off store shelves and focused more on protecting consumers than minimizing costs (Rehak, 2002). Conversely, we believe companies, which have a controlled and externally focused culture, will focus most of their efforts on minimizing costs. Consider, for example, how GM responded to recent quality issues. The "GM salute" and the "GM nod" is suggested to have manifested "deep-seated cultural issues that meant employees would rather sweep a possibly fatal design flaw under the rug than alert upper management" (Gara, 2014). Reports note, for instance,
The quirks of GM's culture may have shaped its response to the faulty switch ... the report describes a troubling mixed message subtly conveyed by senior leadership: that safety is paramount, yet so is keeping a lid on costs. (Colias, 2014)
We believe that a firm's culture shapes how it responds to potential quality failures. Indeed, we conjecture that if firms shift their culture from controlled and externally focused to flexible and internally focused, they may be less likely to experience product recalls and/or may implement more comprehensive product recall processes. Mary Barra (GM's CEO) recently noted that GM is trying to change their culture from a "cost culture" (controlled and externally focused) to more of a "customer culture that focuses on safety and quality" (flexible and internally focused) (WSJ, 2014). Perhaps Mary Barra recognizes the influence that organizational culture can have on a firm's product quality and recall efforts?
As highlighted in the quote above, senior leadership often influences or helps shape an organization's culture. As such, it may be particularly interesting for scholars to consider how a firm's culture and TMT impact the likelihood of product recalls and/or influence how firms respond to recalls. Examining both factors in isolation could reveal key insights, but examining them together could help scholars capture a more holistic understanding of product recalls.
Supply Chain Complexity. One can think of supply chain complexity on a continuum with simple supply chains anchoring one end of the spectrum and complex supply chains anchoring the other end. As supply chains evolve, they move toward the more complex end of the continuum (Dyer & Nobeoka, 2000), which influences a firm's strategic processes as these processes have to change in order to accommodate this increasing complexity. Consequently, as supply chains evolve so too does a firm's product recall processes.
One type of supply chain that is becoming increasingly popular is the omni-channel supply chain (OCSC) (Strang, 2013). OCSCs offer customers the flexibility to shop across various channels (e.g., mobile devices, online, and brick-and-mortar stores) and thus are inherently more complex than other types of chains (e.g., multichannel supply chains). OCSCs require firms to ship products from anywhere in the chain (e.g., distribution center [DC], vendor, store), accept returns from multiple locations (e.g., DC, store), and allow online orders to be picked up in-store. Due to the complexity of product flow, firms may have a harder time executing product recalls in OCSCs than in other types of supply chains. OCSCs may also result in more costly product recalls as firms may have to allocate more resources toward identifying and locating where tainted products are throughout the entire supply chain. Scholars could also examine if the product recall process evolves or unfolds differently depending on the type of supply chain a firm has (e.g., single-channel, multichannel, cross-channel, OCSC). Research in this area could be particularly valuable for scholars and practitioners alike.
Examining the complexity of a firm's supply base could also provide valuable insights into a firm's product recall process. Scholars have primarily focused their attention on how supply base complexity impacts transaction costs, innovation, and performance (e.g., Choi & Krause, 2006). To our knowledge, scholars have not examined the relationship between a firm's supply base complexity and its product recall process. This is somewhat surprising considering that a firm's supply base could play a large role in how a firm responds to a product recall situation. For instance, if a food manufacturer has to recall products due to an ingredient-based issue, it will likely coordinate with firms in their supply base before responding to the situation. Considering that the proportion of product recalls in the food industry due to tainted ingredients and undeclared allergens has increased from 13 percent in 2008 to 35 percent in 2012 (FSIS, 2014), the complexity of a firm's supply base will likely play an increasingly important role in regard to how firms respond to product recalls in the future.
Promising Underutilized Theory. We believe punctuated equilibrium theory can help guide future research on the strategic recall process because it touches upon organizational characteristics as well as system complexity (Gersick, 1991; Tushman & Romanelli, 1985). Punctuated equilibrium theory suggests that systems (i.e., supply chains) exist in a state of equilibrium when there is a normal flow of good products through the system (this period is also referred to as a stasis) (Tushman & Romanelli, 1985) (see Table 3). These equilibrium periods are punctuated (i.e., disrupted) when tainted products breach the chain and cause periods of turbulence during which the firm has to formulate and implement a strategy to help the system return to a state of equilibrium (Miller & Friesen, 1984). The frequency and outcomes of these punctuations are unpredictable, which makes them difficult to manage and is consistent with product recalls (Gersick, 1991).
Although this theory is underutilized in SCM research, it is well-suited to examine product recalls because it focuses on how systems change while considering the "interdependence of organizational subunits" (i.e., supply chain complexity) and "interdependent relationships with buyers, [and] suppliers" (i.e., supply base complexity) (Romanelli & Tushman, 1994; 1144). Punctuated equilibrium theory can provide insights to various units of analysis (e.g., firm, dyad, and network) and thus is an intuitive theoretical lens to examine product recalls (Romanelli & Tushman, 1994).
PRODUCT RECALL IMPACTS
Research in this area also builds on prior literature on the impact of supply chain disruptions in general. However, with product recalls firms face a higher probability of realizing more intangible damage. Thus, while recalls and general supply chain disruptions share certain similarities, their impacts may vary. Only 4 articles (11.8 percent) examined the impacts of product recalls; the majority of the research in this area has focused on the financial consequences of recalls (see Table 1 and Appendix S1). Thirumalai and Sinha (2011), for example, found that the financial impact a firm realizes from a recall depends on several factors, including capital structure (e.g., debt-to-equity ratio), growth prospective, sales, and product scope. The country within which a recall occurs also seems to play a role as Zhao, Li and Flynn (2013) revealed in their research, which suggests Chinese firms realize greater financial impact than their western counterparts.
While most of the research in this area has focused on the negative impacts of product recalls, some scholars have explored the positive effects of recalls. Kalaignanam, Kushwaha and Eilert (2013) and Haunschild and Rhee (2004), for example, found that firms can learn from recalls and thus can modify their operations, which may lead to fewer future recalls. Scholars have made important strides in this area, but there is still much left to explore (see Table 2).
Research Opportunity #3: Learning from Failure and Near-Misses
The literature in related domains suggests that firms can learn from failure (i.e., product recalls); little is known, however, about what conditions foster the most organizational learning postrecall. Kalaignanam et al. (2013) suggest that larger recalls facilitate more organizational learning than smaller recalls, but why is that? Is it because larger recalls provide more motivation for firms to learn from the event to ensure it does not occur again? Perhaps larger recalls receive more media attention and thus firms are forced to investigate those recalls more than smaller, less publicized quality failures. If larger recalls prompt more learning, is there an inflection point where a recall becomes too large or severe, which paralyzes a firm and thus hinders learning?
Although the extant SCM literature suggests a positive relationship between degree of failure (recall severity) and organizational learning, research in related disciplines finds smaller failures promote more learning (e.g., Sitkin, 1992). Hayward (2002), for instance, discovered that firms learn more from acquisitions that result in small losses than from acquisitions associated with great failure or success. One could conjecture that smaller recalls are less intimidating than larger recalls and thus facilitate more learning. Small recalls, however, may be too minor of events to provide sufficient motivation for firms to learn. Perhaps the "best" recalls are small enough to foster learning, but large enough to provide sufficient motivation to change?
We also believe scholars should examine if or how firms learn from near-misses in regard to product quality failures. One school of thought suggests that firms may view near-misses as a "success" and thus are less likely to learn from those events (Dillon & Tinsley, 2008). Others conjecture that near-misses can provide insight into possible accidents or product quality failures and thus enable firms to enhance product quality (e.g., Wu et al., 2010). If firms view feedback they receive from inspections or audits as near-misses, they may be able to learn and thus avoid future product recalls (Anand, Gray & Siemsen, 2012).
Promising Underutilized Theory. Enactment theory focuses on the underlying social and psychological processes through which entities interpret or make sense of their experiences (Weick, 1979). A key aspect of enactment theory is sensemaking, which involves "turning circumstances into a situation that is comprehended explicitly in words that serves as a springboard into action" (Weick, Sutcliffe & Obstfeld, 2005: 409). Said differently, sensemaking refers to "the making of sense" (Weick, 1995: 4) and involves the "structuring of the unknown" (Waterman, 1990: 40). Sensemaking is particularly important, yet challenging in dynamic or turbulent situations, such as product recalls, and can occur at the individual or group (i.e., firm) level. The latter is known as collective sensemaking, which occurs when "individuals exchange provisional understandings and try to agree on consensual interpretations and a course of action" (Stigliani & Ravasi, 2012: 1232). Collective sensemaking is of upmost importance during product recalls because multiple entities along the chain (e.g., buyer and supplier) try to agree on a course of action, such as what products to remove.
Enactment theory helps shed light on how firms interpret complex situations, such as product recalls, in order to understand how to modify their actions in a meaningful way or adapt to changes in the system and/or context (Ellis, Shockley & Henry, 2011; Weick et al., 2005). Enactment theory focuses on reciprocal exchanges between the environment (referred to as ecological change) and actors (known as enactment) and thus is well-suited to examine how firms learn from product recall situations in which actors (firms) are tasked with extracting tainted products from the ecological change (environment).
Another focus of scholars has been on the repertoire of strategic actions firms can take to mitigate the tangible and intangible impacts of product recalls. Consistent with the previous two sections, research on mitigation approaches builds on past scholarship on supply chain disruptions in general. However, only 6 articles (17.6 percent) in the extent literature focused specifically on mitigating the impact of product recalls. Ni, Flynn and Jacobs (2014), for example, found that retailers who opted to respond to a recall via a refund remediation strategy experienced a more significant penalty from the stock market than those that opted for strategies based on a product exchange or repair. This finding is consistent with Davidson and Worrell (1992) that firm value is harmed more when firms replace recalled products or return the purchase price to consumers than when the recalled products are examined and fixed. Speier, Whipple, Closs and Voss (2011) adopted a slightly different perspective by developing a framework with key safety initiatives (process management, information sharing, and relationship management) that can help companies mitigate product safety and security risks.
Scholars have also recently begun examining how firms can mitigate the intangible impacts of product recalls. Zavyalova, Pfarrer, Reger and Shapiro (2012) found that firms receive considerable negative media attention after a product recall. The authors also discovered that technical actions (actions that address the cause of the wrongdoing) employed postrecall were more effective at reducing negative media coverage while ceremonial actions (actions that positively influence impressions about the firm) were more effective at reducing the negative media spillover from recalls by other firms in the industry. Similarly, Van Heerde, Helsen and Dekimpe (2007) found that firms should allocate more resources toward advertising postrecall. Cleeren, Van Heerde and Dekimpe (2013) also examined advertising and pricing strategies postrecall and found that firms must consider: (1) the amount of negative publicity associated with the recall; and (2) the level of responsibility they must acknowledge for the situation. This is a bourgeoning, yet understudied aspect of recalls. As such, there are a number of research opportunities for scholars (see Table 2).
Research Opportunity #4: Organizational Countermeasures
Similar to the strategic recall process, we partitioned this research opportunity into two subelements. The first focuses on the direct effect of product recalls on "guilty" firms (i.e., firms that were directly involved with the recall); the second focuses on the indirect effect of product recalls on "innocent" firms (i.e., firms that were not themselves involved with the recall). We conjecture that the countermeasures firms need to employ to mitigate the impact of a recall vary depending on if the firm is "guilty" or "innocent." The first subelement could also be categorized under product recall impacts and thus is considered a boundary spanning factor.
Direct Effect on "Guilty" Firms. Mitigating the direct impacts of product recalls is arguably one of the most important aspects of the recovery process; however, surprisingly little is known about mitigation strategies and why firms employ the strategies they do. For instance, do firms in the same industry tend to employ the same countermeasures or do firms employ unique mitigation approaches depending on firm idiosyncrasies (e.g., firm location, CEO's background, TMT composition)? Similarly, is the effectiveness of mitigation approaches stable over time or do they vary depending on various contextual factors (e.g., recall severity, type of product being recalled)? Scholars can also examine how the amount of media attention a firm receives during and after a recall influence its mitigation strategy. Do firms implement more countermeasures (e.g., new safety initiatives, more training programs, or terminate employees in key positions) following a highly publicized recall than they do after a less publicized recall?
Collateral Damage on "Innocent" Bystander Firms. Most of the research on mitigation approaches has examined how firms can mitigate the impact of their own products recalls, but there is a lack of understanding about how to mitigate the carryover impact that firms may realize when competitors issue a product recall. Management scholars have examined how wrongdoings, such as financial misconduct (e.g., Paruchuri & Misangyi, 2015), "contaminate" bystander firms in the same industry. There is a dearth of knowledge, however, about the effect product recalls have on "innocent" firms who were not themselves involved in the recall. When firms produce substitutable outputs, they are often considered to be a part of the same industry and thus assumed to have similar processes and characteristics (Barnett & King, 2008). Scholars conjecture that firms in an industry often share a common reputation; this known as the "theory of collective reputations," which builds on the premise that "a group's reputation is only as good as that of its members" (Tirole, 1996: 1). As such, when information (either good or bad) is revealed about one firm, it often reflects or "spills over" (at least to some degree) on all firms in the industry. Although anecdotal evidence suggests that "innocent" firms can suffer when their industry peers experience product recalls (e.g., when Dole recalled their spinach products in 2006, the rest of the spinach industry suffered--Weise & Schmit, 2007), the "collateral damage" from recalls on bystander firms has not been systematically examined. Specifically, do recalls affect "innocent" firms in the same industry? If so, what contextual factors magnify (or alleviate) the effect and how can bystander firms mitigate this collateral damage? Conversely, perhaps there is a "substitution effect" where other firms in the industry benefit from the recall because they can steal consumers and thus increase their market share (e.g., Ni et al., 2014)? Future research in this area could reveal key insights into the system-wide impacts of product recalls.
Promising Underutilized Theories. Justice theory focuses on just and fair interactions between organizations (Rawls, 1971). Justice (fairness) is essential in long-term exchanges between entities and thus plays a central role in regard to if (or how) supply chain partners weather the storm during and after product recalls. Justice theory considers four unique, but complimentary types of justice. The first is procedural justice, which refers to the extent to which a process is perceived to be fair for both parties involved (7) (Thibaut & Walker, 1975). Research suggests that when firms perceive organizational processes to be fair, both entities adopt a higher level of voluntary cooperation based on their attitudes of trust and commitment to the relationship (Kim & Mauborgne, 1998). Simply put, both parties are willing to help mitigate the impact of the recall because they are invested in the partnership and want to see it endure this hardship. Consequently, supply chain partnerships that have a high degree of procedural justice may be able to mitigate the impact of the product recall more effectively than partnerships with a low degree of procedural justice.
Distributive justice refers to fairness of outcomes and originates from the idea of equity (Homans, 1961). Distributive justice focuses on the equitable distribution of outcomes (good or bad) in relation to each entity's actions (Adams, 1965). In a product recall situation, if one party (i.e., supplier) is at fault for the quality failure, they should be primarily responsible for mitigating the impact of the recall on other parties in the chain (i.e., buyer). If the buyer perceives the outcome of the recall to be unjust (i.e., they shoulder more mitigation responsibility than they think is fair), that can result in lack of trust and increased conflict within the buyer-supplier relationship, which can magnify the impact of the recall (Narasimhan, Narayanan & Srinivasan, 2013).
The last two types of justice--interpersonal justice, which refers to perceived fairness during interpersonal interactions (Tyler & Bies, 1990) and informational justice, which refers to perceived fairness of information exchanges (Bies & Moag, 1986)--represent justice during social exchanges. The former centers on the extent to which firms treat their partners with politeness, dignity, and respect when executing processes and determining outcomes (Liu, Huang, Luo & Zhao, 2012). In a recall situation, a buyer-supplier would have a high degree of interpersonal justice if one entity (i.e., buyer) informs the other (i.e., supplier) in a respectful and polite manner of their strategy to mitigate the impacts of the product recall. Conversely, if the buyer implemented the mitigation strategy without informing the supplier or informed the supplier in an impolite or disrespectful manner, there would be a low degree of interpersonal justice.
Informational justice focuses on the extent to which firms distribute accurate and timely information to their supply chain partners about the outcomes of events and/or processes. Information justice is particularly important during and after product recalls because in order to be effective, mitigation actions often have to be employed quickly. If a firm's supply chain partners have accurate and timely information, they may be able to implement countermeasures that help mitigate the impact of the recall. Conversely, if a firm's supply chain partners have inaccurate and/or slow information, they may implement the wrong countermeasure, which could actually increase the impact of the recall. All four types of justice, individually as well as collectively, can help shed light on how firms should interact within their supply chain partners during and after recalls to help mitigate the impacts of product recalls.
This research agenda has implications for academics and practitioners alike and thus appeals to a wide audience. From an academic perspective, the research opportunities discussed above have the potential to facilitate theory development by identifying new variables and proposing new relationships that advance our understanding of product recalls. The research called for in this study is interdisciplinary in nature and thus encourages scholars to explore different explanations and challenge core assumptions on which most (or all) research in this area relies. From a managerial perspective, our study captures key insights from the literature about factors that can lead to recalls, can hinder a firm's product recalls process, and may impact the direct and indirect effects of product recalls (see Table 2). We also provide insight into emergent factors managers should consider moving forward to help reduce the probability of future recalls, to facilitate a firm's recall efforts, and to more effectively mitigate the effects of recalls. While scholars have made important strides in capturing a more holistic understanding of product recalls, there is much left to discover. We hope this research agenda serves as a road map for future research on product recalls, an extremely important, yet underdeveloped research area.
Additional Supporting Information may be found in the online version of this article:
Appendix S1. Overview of Recall Articles in Chronological Order.
Appendix S2. Propositions and Hypotheses Put Forth in Recall Articles.
Journals Searched for Product Recall Articles
Supply Chain/Operations Management/ Logistics Journals
IEEE Transactions on Engineering Management
International Journal of Logistics Management
International journal of Operations and Production Management
International journal of Physical Distribution and Logistics Management
International journal of Production Economics
International journal of Production Research
International Journal of Purchasing and Materials Management
International journal of Quality and Reliability Management
International journal of Quality Science
Journal of Business Logistics
Journal of Operations Management
Journal of Supply Chain Management
Manufacturing and Service Operations Management
Operations Management Research
Production and Operations Management
Total Quality Management
Transportation Research Part E
Administrative Science Quarterly
Academy of Management journal
Academy of Management Review
Strategic Management journal
Journal of Marketing
Journal of Marketing Research
Note: The list of journals included in this study originated from three meta-analyses, including Nair (2006); Mackelprang and Nair (2010); and Wowak, Craighead, Ketchen and Hult (2013). From the list of journals searched in all three meta-analyses, we added four additional journals to our list including Academy of Management Review and Marketing Science (because product recalls can have a large impact on a firm's internal strategy and marketing approach) and Transportation Journal and Transportation Research Part E (because a firm's logistics can significantly impact how efficiently and effectively it can identify and remove tainted products from the chain). To capture a more holistic representation of the extant literature on product recalls, we searched all electronically available issues of the journals instead of specific date ranges.
Acknowledgments: We gratefully acknowledge the valuable comments and suggestions offered by Christopher Craighead, David J. Ketchen, Jr., and Rodney Thomas on an earlier version of this note. Like all invited manuscripts, this note underwent a double-blind peer review.
KAITLIN D. WOWAK
University of Notre Dame
CHRISTOPHER A. BOONE
Georgia Southern University
Adams, J. S. (1965). Inequity in social exchange. In L. Berkowitz (Ed.), Advances in experimental social psychology, Vol. 2 (pp. 267-299). New York, NY: Academic Press.
Alfaro, J. A., & Rabade, L. A. (2009). Traceability as a strategic tool to improve inventory management: A case study in the food industry. International Journal of Production Economics, 118(1), 104-110.
Anand, G., Gray, J., & Siemsen, E. (2012). Decay, shock, and renewal: operational routines and process entropy in the pharmaceutical industry. Organization Science, 23, 1700-1716.
Barnett, M. L., & King, A. A. (2008). Good fences making good neighbors: A longitudinal analysis of an industry self-regulatory institutions. Academy of Management Journal, 51, 1150-1170.
Baysinger, B., & Hoskisson, R. E. (1989). Diversification strategy and R&D intensity in multiproduct firms. Academy of Management Journal, 32, 310-332.
Bies, R. I., & Moag, J. S. (1986). Interactional justice: communication criteria of fairness. In R. J. Lewicki, B. H. Sheppard & M. H. Bazerman (Eds.), Research on negotiation in organizations, Vol. 1 (pp. 43-55), Greenwich, CT: JAI Press.
Blackhurst, J., Dunn, K. S., & Craighead, C. W. (2011). An empirically derived framework of global supply resiliency. Journal of Business Logistics, 32, 374-391.
Bromiley, P., & Marcus, A. (1989). The deterrent to dubious corporate behavior: Profitability, probability and safety recalls. Strategic Management Journal, 10, 233-250.
Cain, M. D., & McKeon, S. B. (in press). CEO personal risk-taking and corporate policies. Journal of Financial and Quantitative Analysis, forthcoming.
Carpenter, M. A., Geletkanycz, M. A., & Sanders, W. G. (2004). Upper echelons research revisited: Antecedents, elements, and consequences of top management team composition. Journal of Management, 30, 749-778.
Chao, G. H., Iravani, S. M., & Savaskan, R. C. (2009). Quality improvement incentives and product recall cost sharing contracts. Management Science, 55, 1122-1138.
Chen, Y., Ganesan, S., & Liu, Y. (2009). Does a firm's product-recall strategy affect its financial value? An examination of strategic alternatives during product-harm crises. Journal of Marketing, 73, 214-226.
Chiarini, A. (2015). Effect of ISO 9001 non-conformity process on cost of poor quality in capital-intensive sectors. International Journal of Quality and Reliability Management, 32, 144-155.
Choi, T. Y., & Krause, D. R. (2006). The supply base and its complexity: Implications for transaction costs, risks, responsiveness, and innovation. Journal of Operations Management, 24, 637-652.
Cleeren, K., Van Heerde, H. J., & Dekimpe, M. G. (2013). Rising from the ashes: How brands and categories can overcome product-harm crises. Journal of Marketing, 77, 58-77.
Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20(1), 37-46.
Colias, M. (2014). Report fingers GM culture as a culprit. http://www.autonews.com/article/20140607/ OEM 11/306099953/report-fingers-gm-culture-asa-culprit. Accessed July 1, 2014.
Connelly, B. L., Ketchen, Jr, D. J., & Slater, S. F. (2011). Toward a "theoretical toolbox" for sustainability research in marketing. Journal of the Academy of Marketing Science, 39(1), 86-100.
Daily, C. M., Certo, S. T., & Dalton, D. R. (2000). International experience in the executive suite: The path to prosperity? Strategic Management Journal, 21, 515-523.
Das, K. (2011). A quality integrated strategic level global supply chain model. International Journal of Production Research, 49(1), 5-31.
Davidson, W. N., & Worrell, D. L. (1992). Research notes and communications: The effect of product recall announcements on shareholder wealth. Strategic Management Journal, 13, 467-473.
Deshpande, R., Farley, J. U., & Webster, Jr., F. E. (1993). Corporate culture, customer orientation, and innovativeness in Japanese firms: A quadrad analysis. Journal of Marketing, 57(1), 23-37.
Dillon, R. L., & Tinsley, C. H. (2008). How near-misses influence decision making under risk: A missed opportunity for learning. Management Science, 54, 1425-1440.
Dyer, J. H., & Nobeoka, K. (2000). Creating and managing a high-performance knowledge-sharing network: The Toyota case. Strategic Management Journal, 21, 345-367.
Eichenberger, S. (2011). In pictures: 15 oldest family companies, http://www.forbes.com/2011/06/17/ oldest-family-businesses_slide_5. html. Accessed April 12, 2015.
Ellis, S. C., Shockley, J., & Henry, R. M. (2011). Making sense of supply disruption risk research: A conceptual framework grounded in enactment theory. Journal of Supply Chain Management, 47, 65-96.
Epelbaum, F. M. B., & Martinez, M. G. (2014). The technological evolution of food traceability systems and their impact on firm sustainable performance: A RBV approach. International Journal of Production Economics, 150, 215-224.
FDA. (2009). Safety: background and definitions. http://www.fda.gov/Safety/Recalls/ ucml65546.htm. Accessed March 23, 2015.
FSIS. (2014). FSIS Compliance Guidelines, http:// www.fsis.usda.gov/wps/wcm/connect/f9cbb0e96b4d-4132-ae27-53e0b52e840e/Allergens-Ingredi- ents.pdf?MOD=A)PERES. Accessed April 17, 2015.
Gara, A. (2014). GM proves bankruptcy is no cure for sick culture. http://www.thestreet.com/story/ 12739514/ 1/general-motors-bankruptcy-doesntcure-culture.html. Accessed July 1, 2014.
Gersick, C. J. G. (1991). Revolutionary change theories: a multi-level exploration of the punctuated equilibrium paradigm. Academy of Management Review, 16(1), 10-36.
GMA. (2011). Capturing recall costs: Measuring and recovering the losses, http://www.gmaonline.org/ file-manager/images/gmapublications/Capturing_Recall_Costs_GMA_Whitepaper_FINAL.pdf. Accessed December 5, 2014.
Guthrie, J. P., & Datta, D. K. (1997). Contextual influences on executive selection: Firm characteristics and CEO experience. Journal of Management Studies, 34, 537-560.
Hambrick, D. C. (2007). Upper echelons theory: An update. Academy of Management Review, 32, 334-343.
Hambrick, D. C., & Mason, P. A. (1984). Upper echelons: The organization as a reflection of its top managers. Academy of Management Review, 9, 193-206.
Haunschild, P. R., & Rhee, M. (2004). The role of volition in organizational learning: The case of automotive product recalls. Management Science, 50, 1545-1560.
Hayward, M. (2002). When do firms learn from their acquisition experience? Evidence from 19901995. Strategic Management Journal, 23(1), 21-39.
Hendricks, K. B., Hora, M., & Singhal, V. R. (in press). An empirical investigation on the appointments of supply chain and operations management executives. Management Science, forthcoming.
Homans, G. C. (1961). Social behavior: its elementary forms. New York, NY: Harcourt. Brace and World.
Hora, M., Bapuji, H., & Roth, A. V. (2011). Safety hazard and time to recall: The role of recall strategy, product defect type, and supply chain player in the U.S. toy industry. Journal of Operations Management, 29, 766-777.
Huff, A. S., & Reger, R. K. (1987). A review of strategic process research. Journal of Management, 13(2), 211-236.
Kalaignanam, K., Kushwaha, T., & Eilert, M. (2013). The impact of product recalls on future product reliability and future accidents: Evidence from the automobile industry. Journal of Marketing, 77(2), 41-57.
Ketchen, Jr, D. J., Wowak, K. D., & Craighead, C. W. (2014). Resource gaps and resource orchestration shortfalls in supply chain management: The case of product recalls. Journal of Supply Chain Management, 50, 6-15.
Kiani, B., Shirouyehzad, H., Khoshsaligheh Bafti, F., & Fouladgar, H. (2009). System dynamics approach to analyzing the cost factors effects on cost of quality. International Journal of Quality and Reliability Management, 26, 685-698.
Kim, W. C., & Mauborgne, R. (1998). Procedural justice, strategic decision making, and the knowledge economy. Strategic Management Journal, 19, 323338.
Kumar, S., & Schmitz, S. (2011). Managing recalls in a consumer product supply chain-root cause analysis and measures to mitigate risks. International Journal of Production Research, 49(1), 235-253.
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159-174.
Laufer, D., & Jung, J. M. (2010). Incorporating regulatory focus theory in product recall communications to increase compliance with a product recall. Public Relations Review, 36, 147-151.
Levick, R. (2011). A survival map of the age of product recalls. Forbes, http://www.forbes.com/sites/ richardlevick/2011/08/17/a-survival-map-in-theage-of-product-recalls/. Accessed July 1, 2014.
Li, J., & Tang, Y. 1. (2010). CEO hubris and firm risk taking in China: The moderating role of managerial discretion. Academy of Management Journal, 53 (1), 45-68.
Li, Y., Wang, L., & Liu, Y. (2011). Organisational learning, product quality and performance: The moderating effect of social ties in Chinese cross-border outsourcing. International Journal of Production Research, 49(1), 159-182.
Liu, Y., Huang, Y., Luo, Y., & Zhao, Y. (2012). How does justice matter in achieving buyer-supplier relationship performance? Journal of Operations Management, 30, 355-367.
Macdonald, C., Lynch, J., & Burden, M. (2014). As victims are identified in crashes tied to GM recall, families want info. The Detroit News, http:// www.detroitnews.com/ artide/20140411/ AUTO0103/304110092. Accessed April 4, 2015.
Mackelprang, A. W., & Nair, A. (2010). Relationship between just-in-time manufacturing practices and performance: A meta-analytic investigation. Journal of Operations Management, 28, 283-302.
Marucheck, A., Greis, N., Mena, C., & Cai, L. (2011). Product safety and security in the global supply chain: Issues, challenges and research opportunities. Journal of Operations Management, 29, 707-720.
McDermott, C. M., & Stock, G. N. (1999). Organizational culture and advanced manufacturing technology implementation. Journal of Operations Management, 17(5), 521-533.
Miller, D., & Friesen, P. H. (1984). Organizations: A quantum view. Englewood Cliffs, NJ: Prentice-Hall.
Nair, A. (2006). Meta-analysis of the relationship between quality management practices and firm performance--Implications for quality management theory development. Journal of Operations Management, 24, 948-975.
Narasimhan, R., Narayanan, S., & Srinivasan, R. (2013). An investigation of justice in supply chain relationships and their performance impact. Journal of Operations Management, 31, 236-247.
Neuendorf, K. A. (2002). The content analysis guidebook. Thousand Oaks, CA: Sage.
Newbert, S. (2007). Empirical research on the resource-based view of the firm: An assessment and suggestions for future research. Strategic Management Journal, 28(2), 121-146.
Ni, J. Z., Flynn, B. B., & Jacobs, F. R. (2014). Impact of product recall announcements on retailers' financial value. International Journal of Production Economics, 153, 309-322.
Paruchuri, S., & Misangyi, V. F. (2015). Investor perceptions of financial misconduct: The heterogeneous contamination of bystander firms. Academy of Management Journal, 58(1), 169-194.
Powell, T. C. (1995). Total quality management as competitive advantage: A review and empirical study. Strategic Management Journal, 16(1), 15-37.
Rawls, J. (1971). A theory of justice. Cambridge, MA: Belknap Press of Harvard University Press.
Rehak, J. (2002). Tylenol made a hero of Johnson and Johnson: The recall that started them all. http://www.nytimes.com/2002/03/23/yourmoney/23iht-mjj_ed3_.html. Accessed April 12, 2015.
Resende-Filho, M. A., & Hurley, T. M. (2012). Information asymmetry and traceability incentives for food safety. International Journal of Production Economics, 139, 596-603.
Romanelli, E., & Tushman, M. (1994). Organizational transformation as punctuated equilibrium: An empirical test. Academy of Management Journal, 37 (5), 1141-1166.
Roth, A. V., Tsay, A. A., Pullman, M. E., & Gray, J. V. (2008). Unraveling the food supply chain: Strategic insights from China and the 2007 recalls. Journal of Supply Chain Management, 44(1), 22-30.
Rungtusanatham, M., Anderson, J. C., & Dooley, K. J. (1997). Conceptualizing organizational implementation and practice of statistical process control. Journal of Quality Management, 2(1), 113-137.
Sitkin, S. (1992). Learning through failure: The strategy of small losses. Research in Organizational Behavior, 14, 231-266.
Skilton, R., & Robinson, J. (2009). Traceability and normal accident theory: How does supply network complexity influence the traceability of adverse events? Journal of Supply Chain Management, 45, 40-53.
Speier, C., Whipple, J. M., Closs, D. J., & Voss, M. D. (2011). Global supply chain design considerations: Mitigating product safety and security risks. Journal of Operations Management, 29(7), 721-736.
Steven, A. B., Dong, Y., & Corsi, T. (2014). Global sourcing and quality recalls: An empirical study of outsourcing-supplier concentration-product recalls linkages. Journal of Operations Management, 32(5), 241-253.
Stigliani, I., & Ravasi, D. (2012). Organizing thoughts and connecting brains: Material practices and the transition from individual to group-level prospective sensemaking. Academy of Management Journal, 55, 1232-1259.
Strang, R. (2013). Retail without boundaries. Supply Chain Management Review, 17, 32-39.
Thibaut, J., & Walker, L. (1975). Procedural justice: a psychological analysis (1st ed.). Hillsdale, NJ: Erlbaum.
Thirumalai, S., & Sinha, K. K. (2011). Product recalls in the medical device industry: An empirical exploration of the sources and financial consequences. Management Science, 57, 376-392.
Tirole, J. (1996). A theory of collective reputations (with applications to the persistence of corruption and to firm quality). Review of Economics Studies, 63(1), 1-22.
Tse, Y. K., & Tan, K. H. (2011). Managing product quality risk in a multi-tier global supply chain. International Journal of Production Research, 49(1), 139-158.
Tse, Y. K., & Tan, K. H. (2012). Managing product quality risk and visibility in multi-layer supply chain. International Journal of Production Economics, 139(1), 49-57.
Tushman, M., & Romanelli, E. (1985). Organizational evolution: a metamorphosis model of convergence and reorientation. In L. L. Cummings & B. M. Staw (Eds.), Research in organizational behavior, 7 (pp. 171-222). Greenwich, CT: JAI Press.
Tyler, T. R., & Bies, R. I. (1990). Beyond formal procedures: the interpersonal context of procedural justice. In J. Carroll (Ed.), Applied Social Psychology and Organizational Settings (pp. 77-98). Hillsdale, NJ: Erlbaum.
Van Heerde, H., Helsen, K., & Dekimpe, M. G. (2007). The impact of a product-harm crisis on marketing effectiveness. Marketing Science, 26, 230-245.
Van Iwaarden, J., & Van der Wiele, T. (2012). The effects of increasing product variety and shortening product life cycles on the use of quality management systems. International Journal of Quality and Reliability Management, 29, 470500.
Wang, X., Li, D., & O'Brien, C. (2009). Optimisation of traceability and operations planning: An integrated model for perishable food production. International Journal of Production Research, 47, 2865-2886.
Wang, X., Li, D., O'Brien, C., & Li, Y. (2010). A production planning model to reduce risk and improve operations management. International journal of Production Economics, 124, 463-474.
Waterman, Jr, R. H. (1990). Adhocracy: The power to change. Memphis, TN: Whittle Direct Books.
Weick, K. E. (1979). The social psychology of organizing (2nd edn.) Reading, MA: Addison-Wesley.
Weick, K. E. (1995). Sensemaking in organizations (Vol. 3). Thousand Oaks, CA: Sage.
Weick, K. E., Sutcliffe, K. M., & Obstfeld, D. (2005). Organizing and the process of sensemaking. Organization Science, 16, 409-421.
Weise, E., & Schmit, J. (2007). Spinach recall: 5 faces. 5 agonizing deaths. 1 year later. http://usatoday30.usatoday.com/money/industri es/food/200709-20-spinach-main_n.htm. Accessed July 1, 2014.
Wowak, K. D., Craighead, C. W., Ketchen, Jr, D. J., & Hult, G. T. M. (2013). Supply chain knowledge and performance: A meta-analysis. Decision Sciences, 44, 843-875.
Wowak, A. J., & Hambrick, D. C. (2010). A model of person-pay interaction: How executives vary in their responses to compensation arrangements. Strategic Management journal, 31, 803-821.
Wowak, A. J., Mannor, M. J., & Wowak, K. D. (2015) Throwing caution to the wind: The effect of CEO stock option pay on the incident. Strategic Management journal, 36, 1082-1092.
WSJ. (2014). The culture of general motors, http:// online.wsj.com/news/articles/SB1000142405270 230398 7004579479563171510386. Accessed July 1, 2014.
Wu, W., Yang, H., Chew, D. A., Yang, S. H., Gibb, A. G., & Li, Q. (2010). Towards an autonomous real-time tracking system of near-miss accidents on construction sites. Automation in Construction, 19, 134-141.
Yaros, R. S., & Wood, D. F. (1979). Recalling products in the drug and cosmetic industry, journal of Business Logistics, 1, 48-59.
Zavyalova, A., Pfarrer, M. D., Reger, R. K., & Shapiro, D. L. (2012). Managing the message: The effects of firm actions and industry spillovers on media coverage following wrongdoing. Academy of Management journal, 55, 1079-1101.
Zhao, X., Li, Y., & Flynn, B. B. (2013). The financial impact of product recall announcements in China. International journal of Production Economics, 142(1), 115-123.
(1) The Food and Drug Administration (FDA) defines recalls as "actions taken by a firm to remove a product from the market" (FDA, 2009) and uses three classes to denote the level of severity of a particular recall situation. Recalls can also be voluntary (a firm recalls a product) or involuntary (a firm is mandated to recall a product by governmental agencies). In this study, we consider all three classes of product recalls as well as voluntary and involuntary recalls.
(2) Traceability plays an intricate role in a firm's ability to identify and remove tainted products from the chain. We therefore included articles that considered traceability in regard to product safety. Articles that examined traceability, but were tangentially related to recalls fell outside the scope of this research and thus were not included.
(3) We searched each of the journal's online archives as well as the ABI/Inform database. Also, similar to Newbert (2007), we only considered published journal articles; dissertations/theses and working papers were not included.
(4) To capture a more nuanced perspective of past scholarship, we partitioned empirical research into three categories: (1) qualitative; (2) secondary data; and (3) survey.
(5) The crude intercoder agreement (percentage agreement) was .90 for article focus, .97 for unit of analysis, and 1.00 for methodology; Neuendorf (2002: 166) classifies all three percentages as "acceptable to all." We also calculated intercoder reliability via Cohen's Kappa (Cohen, 1960), which accounts for the probability of chance agreement. The intercoder reliabilities were .75 for article focus, .93 for unit of analysis, and 1.00 for methodology; Landis and Koch (1977: 165) refer to all three as "almost perfect."
(6) Scholars could also consider top executives in similar positions, such as Vice President (VP) of Purchasing, VP of Procurement, VP of Logistics, and/or VP of Global Supply Chain Management to name a few.
(7) For simplicity of discussion, we assume that only two parties are involved in an exchange (i.e., buyer and supplier), but the underlying arguments can be extended to X number of entities.
Kaitlin D. Wowak (Ph.D., The Pennsylvania State University) is Assistant Professor of Management at the University of Notre Dame. Her research interests include: product recalls, supply chain risks and disruptions, organizational learning and knowledge, and strategic sourcing/procurement.
Christopher A. Boone (Ph.D., Auburn University) is Assistant Professor of Logistics at Georgia Southern University. His research interests include supply chain risks and disruptions, closed loop supply chains, logistics service quality, and transportation.
TABLE 1 Product Recall Article Matrix Product Recall Stages Product Product Recall Recall Method (a) Precursors Process Unit of Firm Empirical (Q) 3 (8.8%) 2 (5.9%) Analysis Level Empirical (SD) 2 (5.9%) 2 (5.9%) Empirical (S) 2 (5.9%) 1 (2.9%) Analytical Model 1 (2.9%) Descriptive Conceptual Dyad Empirical (Q) Level Empirical (SD) Empirical (S) Analytical Model 4 (11.8%) Descriptive Conceptual Network Empirical (Q) Level Empirical (SD) 1 (2.9%) Empirical (S) Analytical Model 2 (5.9%) Descriptive 1 (2.9%) Conceptual 1 (2.9%) Total 15 (44.1%) 7 (20.6%) Product Recall Stages Product Recall Mitigation Method (a) Impacts Approaches Unit of Firm Empirical (Q) Analysis Level Empirical (SD) 4 (11.8%) 4 (11.8%) Empirical (S) 1 (2.9%) Analytical Model 1 (2.9%) Descriptive Conceptual Dyad Empirical (Q) Level Empirical (SD) Empirical (S) Analytical Model Descriptive Conceptual Network Empirical (Q) Level Empirical (SD) Empirical (S) Analytical Model Descriptive Conceptual Total 4 (11.8%) 6 (17.6%) Four articles considered multiple aspects of product recalls; these articles were placed in the category that they focused primarily on and thus only appear once in the table. We also excluded both research agendas (see Appendix S1) from the table because these articles center on recalls in general rather than a specific stage. (a) Empirical: Q = qualitative; SD = secondary data; S = survey. TABLE 2 Overview of Findings in the Literature and Road Map for Future Research Recall Research Aspect Opportunities Findings in the Literature Product Top Management * CEO compensation may lead to a higher Recall Teams probability of firms experiencing Precursors product recalls (e.g., Wowak et al., 2015). * The possibility of being "punished" via abnormal stock market reactions from dubious behavior, such as releasing defective products into the market, may be insufficient to deter management from executing such behaviors (e.g., Bromiley & Marcus, 1989). * Contracts established by managers may impact product quality in interfirm relationships, which can lead to product recalls (e.g., Chao et al., 2009). * Managers that integrate product safety-related traceability with operations management processes can enhance traceability and manufacturing performance while reducing product quality risks (e.g., Wang et al., 2010). Product Organizational * The time it takes for firms to recall Recall Culture products depends on: (1) their recall Process strategy (proactive vs. reactive); (2) type of defect (manufacturing defect vs. design flaw); and (3) the recalling firm (manufacturer, distributor, retailer) (e.g., Hora et al., 2011). * Firms can use different types of recall processes, such as proactive recall and reactive (passive) recall processes (e.g., Chen et al., 2009). * Firms experience different types of recalls (e.g., Ketchen et al., 2014). Supply Chain * A firm's sourcing strategy may impact Complexity a firm's product recall efforts and recall process (e.g., Steven et al., 2014). * Traceability capabilities may provide both qualitative and quantitative benefits and can facilitate the recall process (e.g., Alfaro & Rabade, 2009). * Traceability capabilities are increasingly important to the recall process due to product proliferation and shortened product life cycles (e.g., Van Iwaarden & Van der Wiele, 2012). * The type of supply network (linear or complex) impacts a firm's traceability and thus impacts its product recall process (e.g., Skilton & Robinson, 2009). Product Learning from * Firms learn more from voluntary Recall Failure and recalls than from involuntary recalls Impacts Near-Misses (e.g., Haunschild & Rhee, 2004). * Firms that experience a large recall tend to realize fewer and less severe future recalls (e.g., Kalaignanam et al., 2013). * Both Chinese and Western firms experience negative returns as the result of product recalls. Recalls, however, are a fairly new phenomena in China and thus Chinese firms seem to experience a more negative impact (e.g., Zhao et al., 2013). * Firms that recall medical devices tend to experience fewer future recalls, which suggests a learning effect (e.g., Thirumalai & Sinha, 2011). Mitigation Mitigating * Firms must consider both the extent of Approaches Direct and the negative publicity associated with a Indirect recall and the level of responsibility Product Recall they must accept for the recall when Effects selecting postrecall advertising and pricing strategies (e.g., Cleeren et al., 2013). * Firms that opt to examine and repair recalled products are able to reduce the harmful effect of product recalls more effectively than those that offer to replace the product refund the purchase price (e.g., Davidson & Worrell, 1992) * Technical actions by firms postrecall reduce negative media attention while ceremonial actions by firms are more effective at reducing negative media spillover from recalls by other firms in the industry (e.g., Zavyalova et al.. 2012). * Firms must significantly increase their investment in advertising after a recall to successfully recoup from the crisis and to reduce their vulnerability to competitors (e.g.. Van Heerde et al., 2007). Recall Research Aspect Opportunities Road Map for Future Research Product Top Management * What impact does CEO experience have Recall Teams on the probability a firm experiences Precursors product recalls? Are firms with CEOs who have an operational background less likely to have product recalls than firms with CEOs who have nonoperational (e.g., marketing, accounting) backgrounds? * Does TMT composition impact the likelihood of firms experiencing product recalls? Are firms with a chief supply chain officer (CSCO) less likely to experience product recalls than firms without a CSCO? If so, why? Do CSCOs help firms strategically cut operating costs while maintaining product quality? * What "punishments" (e.g., legal fees, government sanctions, tarnished reputation) are sufficient to deter dubious behavior on behalf of executives? Are "punishments" uniform across all industries or do certain industries "punish" firms/managers more so than other industries? If so, do firms in the latter industries experience fewer recalls? * What incentives can increase or reduce product quality issues between firms? Can manufacturers employ certain mechanisms to help lower the probability of product quality issues on behalf of their suppliers? Product Organizational * What role does organizational culture Recall Culture play in regard to a firm's product Process recall strategy? * Do certain organizational cultures lead to more effective product recalls while other cultures lead to more fragmented recalls? * Does a firm's organizational culture influence how likely a firm is to experience product recalls? Perhaps firms with a controlled, externally focused culture have a higher probability of experiencing product recalls than firms with a flexible, internally focused culture? Similarly, perhaps risk seeking firms or firms that are more competitive have a higher probability of experiencing product recalls than firms that are risk- averse? Supply Chain * Does the product recall process unfold Complexity differently depending on the entities involved and/or the complexity of a firm's supply chain? * Are product recall processes harder to execute in highly complex supply chains, such as omni-channel supply chains? * How do traceability capabilities help firms effectively identify and remove counterfeit products from the chain? Are traceability systems designed for product recalls equally valuable in regard to identifying and removing counterfeit products? * Supply chains are designed to optimize the forward flow of products and therefore do not often operate efficiently when products need to flow back upstream. Consequently, how can supply chains be redesigned to facilitate the flow of products back upstream during product recalls? * When does integrating traceability and operations management processes increase product quality risks? Perhaps under certain conditions traceability and operations management processes have competing factors and thus, if integrated, could increase the probability of a product recall? Product Learning from * What conditions foster the most Recall Failure and learning postrecall? Do particularly Impacts Near-Misses large recalls yield the most learning or are they too severe and thus paralyze organizational learning? Are smaller recalls less intimidating and thus result is more learning or are they too minor to prompt organizational learning? * What (if any) learning "spillover" effect is there for other firms in the same industry and/or product category who were not involved in the recall? In other words, do firms have to endure a product recall to learn from it or can they learn from other firm's "mistakes"? * While a number of studies have explored the impact of product recalls from the shareholder perspective (i.e., stock prices), little is known about how recalls impact other stakeholders (e.g., consumers). * Does a proactive recall strategy always have a more negative effect on shareholder wealth? Perhaps the impact of a proactive recall strategy depends on contextual factors (e.g., industry or product being recalled)? * What are the system-wide impacts of recalls on all supply chain members (other than the manufacturer)? Are retailers "punished" or does most (or all) of the impact fall on the manufacturer? Mitigation Mitigating * How do product recalls affect Approaches Direct and bystander firms in the same industry who Indirect were not themselves involved in the Product Recall recall? Is there a "collateral damage" Effects effect or a "substitution" effect? If there is "collateral damage," how can "innocent" firms mitigate it? * Do firms in the same industry implement similar countermeasures? If so, do the countermeasures become less effective over time? * Does the effectiveness of a firm's mitigation approaches vary by contextual factors, such as industry (e.g., fast- paced vs. slow-paced), brand profile (e.g., well-known brand vs. little- known brand), or product type (e.g., food product vs. children's toy)? * What mechanisms can firms employ to help mitigate the negative impact of product recalls on shareholder wealth? * Do firms experience less negative media attention after product recalls that are caused by their supply chain partners? A recent recall by Aston Martin, for example, was due to counterfeit plastic their supplier used in the manufacturing process. Because Aston Martin was "innocent" will the negative media attention fall primarily on their supplier? * Does CEO experience and/or TMT composition influence a firm's mitigation strategy? Perhaps CEOs who have an operational background are more likely to implement technical actions while CEOs who have an advertising background are more likely to implement ceremonial actions postrecall? TABLE 3 Underutilized Theories for Future Product Recall Studies Research Seminal Recall Aspect Opportunities Theory Citation(s) Product Recall Top Management Upper Echelons Hambrick and Precursors Teams Theory Mason (1984) Product Recall Organizational Punctuated Gersick (1991); Process Culture Equilibrium Tushman and Theory Romanelli Supply Chain (1985) Complexity Product Recall Learning from Enactment Weick (1979) Impacts Failure and Theory Near-Misses Mitigation Mitigating Direct Justice Rawls (1971) Approaches and Indirect Theory Impacts Key Insights into Recall Aspect Key Tenets of Theory Product Recalls Product Recall Upper echelons theory Upper echelons theory Precursors suggests that a firm's can shed light about strategic choices and why certain firms performance is continuously struggle partially determined by with product recalls the background while other firms go characteristics of the long periods without firm's top management any quality issues. team. Product Recall Punctuated equilibrium Punctuated equilibrium Process theory focuses on how theory can shed light systems evolve or on how firms should change over time. This manage punctuations theory suggests that (i.e., product recalls) systems experience that interrupt periods of stability equilibrium periods and (equilibrium periods), disrupt product flow. which are punctuated by short revolutionary periods that disrupt normal activity patterns. Product Recall Enactment theory Enactment theory can Impacts focuses on the provide insight into psychological and how firms derive social processes meaning from or make through which entities sense of product interpret or make sense recalls, which can play of their experiences. a large role in their postrecall recovery strategies. Mitigation Justice theory centers Justice theory can Approaches on fairness between provide guidance about supply chain partners how entities along the and considers four supply chain should types of justice: (1) manage the product interpersonal justice, recall process and how fairness during they should share the interpersonal impacts of product interactions; (2) recalls in a just and informational justice, fair manner to mitigate fairness in regard to the overall effects of communication of product recalls. information; (3) distributive justice, fairness of outcomes; and (4) procedural justice, fairness of the process.
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|Author:||Wowak, Kaitlin D.; Boone, Christopher A.|
|Publication:||Journal of Supply Chain Management|
|Article Type:||Statistical table|
|Date:||Oct 1, 2015|
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