Search results

The authors provide an example of a group of online shoppers exploiting a pricing mistake and exploring the drivers of predatory shopping that may harm online retailers. This paper aims to examine the role of social vigilantism, proactivity and self-presentation in driving individual predatory shopping behaviors and delivers a broader understanding of how these behaviors develop in online communities.

The authors use a mixed-methods sequential research model. In Study 1, the authors explore predatory shopping by using a netnographic textual approach to analyze an online forum engaging in predatory shopping. In Study 2, the authors empirically analyze the uncovered conceptual findings using the PROCESS macro.

Customers who engage in predatory shopping online exhibit social vigilantism when communicating their views to others and proactively seeking out pricing mistakes and opportunities. Customers engaging in predatory shopping adapt their presentation online to increase their chances of success; this effect is strengthened by the online disinhibition effect.

Predatory shoppers can actively seek out pricing mistakes online, encourage participation and exploit mistakes by adapting their self-presentation. Therefore, online retailers should be proactive and consistent when communicating with customers and collaborating to deter predatory shopping. In addition, online retailers should focus on building advocates in communities to prevent harm from predatory shoppers online.

Online predatory shopping is explored qualitatively and quantitatively to understand the propensities that can drive predatory behavior and provide warning signs for online retailers. In addition, the effects of predatory shopping drivers are analyzed in the presence of the online disinhibition effect.

This paper aims to identify the ways that customers respond to customer-to-customer comparisons that may drive loyal customers to engage in undesirable behaviors. The research examines the role that jealousy and envy play in restoring equity through revenge-seeking intentions.

The study uses survey research methodology. The measurement model is validated using CFA, and hypotheses are tested using structural equation modeling. The mediated relationships are calculated using the bootstrap method, and moderated mediation is calculated by creating estimands to test the effects.

Customers who feel either jealousy or envy may engage in revenge-seeking behaviors, such as vindictive complaining and negative electronic word-of-mouth (eWOM). Customers who perceive that a firm is unfairly favoring other customers develop feelings of jealousy and betrayal, and this tendency is strengthened when the customer has a high level of prior trust. Customers typically develop envy when their attention and perceptions of inequity center on another customer, rather than on the firm’s actions and anger drives this effect.

Customers can pursue revenge-seeking actions when unfair actions influence the formation of envy and jealousy through the development of perceived betrayal. Companies can focus on the comparisons that customers make to address revenge-seeking and better manage online relationships preemptively.

The paths that customers take to revenge through jealousy and envy are conceptualized in a communal relationship setting and further developed. Further distinctions of jealousy and envy are made, and the role of prior trust in enhancing revenge-seeking is found.

Supply chain management (SCM) proficiency is generally associated with superior business performance. Yet, SCM research continues to focus predominantly on the performance of individual firms, rather than on the collective performance of multiple supply chain participants as espoused by the extended enterprise (EE) concept. In response to calls for quantitative studies that examine the collective performance of multiple supply chain participants, this research study compares the combined performance of triads comprising focal firms recognized for their relative SCM proficiency and their upstream (supplier) and downstream (customer) supply chain partners with that of their close industry competitors' triads.

The triadic, longitudinal examination of multiple supply chain participants' collective performance utilized archival financial data of the period 2007–2017 from the Compustat database and the supply chain (SPLC) function of Bloomberg.

Findings of this study indicated that supply chain triads that included focal firms recognized for their relative SCM proficiency experienced significantly lower sales and general administrative expenses and significantly higher productivity, return on assets and profitability over time than their close industry competitors' triads. However, contrary to expectations, the performance advantages identified did not extend to revenue growth.

Supply chain triads cannot fully represent entire supply chains or EEs. However, this study’s triadic analysis can be viewed as a practically achievable proxy for further validating the EE concept. Moreover, based on assertions that triadic studies are suitable for SCM research and on empirical studies that consistently show individual firms recognized for their relative SCM proficiency outperform competitors, the authors contend that the study’s findings appropriately corroborate the value of the EE concept.

Because such empirical evidence is so rare, the consistent, collective performance advantages identified in this study should be highly significant to managers.

Robust, longitudinal evidence that supply chain triads which include focal firms recognized for relative SCM proficiency collectively outperform their close industry competitors' triads extends generally accepted associations between SCM proficiency and business performance, suggesting that the application of extended resource-based view (ERBV) in supply chain contexts warrants further examination and further substantiates the efficacy of the EE concept.

This research study aims to investigate consumer usage motivations for three of the top social media platforms today: Facebook, Twitter and Instagram. Additionally, through understanding various platform distinctions, firms can understand which social media platforms consumers prefer to use to co-create with brands online.

An exploratory qualitative study is first conducted to understand consumer motivations for using different social media platforms. The main study tests five hypotheses related to consumer usage intentions and social media co-creation behavior across three social media platforms. A survey is conducted with 1,050 social media users with a comparison of mean responses using multivariate analysis of covariance.

Results support significant differences between platforms in terms of use and co-creation behaviors. For informational purposes, consumers gravitate toward Twitter. For social purposes, Twitter and Instagram are preferred. Instagram is the primary platform for entertainment motivation as well as co-creating with brands via social media. Surprisingly, Facebook shows the lowest usage intentions and co-creation despite being the largest platform and network most widely used by marketers.

To the best of the authors’ knowledge, this is one of the first studies to take a multi-platform approach to understanding consumer social media use and co-creation with brands. The results highlight that marketing academics and practitioners must segment the various social media platforms as each offers unique value propositions to consumers.

A firestorm is a vast wave of negative information about a brand that disseminates quickly online. Their relative unpredictability represents a particularly challenging problem for brand marketers. This paper aims to show how firestorms are enabled and can be disabled by online community members (OCMs), exploring the dissemination of negative electronic word-of-mouth (e-WOM), the challenges in countering negative brand information and how brands can effectively communicate with OCMs to facilitate offsetting negative e-WOM.

This paper uses a sequential mixed-method research methodology. Study 1 uses an experimental design and tests serial mediation using PROCESS Model 6. Study 2 extends the findings while introducing a moderator using the PROCESS Model 83. Finally, qualitative findings are used to develop a practitioner-friendly typology of OCMs.

The perceived authenticity of a message can influence the believability of negative WOM in the presence of a negative availability cascade. Positive cascades are likely to prevent online communities from enabling negative e-WOM when the instigating message is perceived to be inauthentic. Qualitative findings from a post hoc analysis identify a typology of eight OCM types that enable and are also capable of disabling firestorms.

OCMs can both actively fuel and cool a firestorm. Brands should always monitor online communities and closely monitor discussions that are most likely to generate firestorms. More proactively, they should also develop communication strategies for each OCM type to help disable firestorms in the making.

Both negative and positive cascades are explored quantitatively and qualitatively to understand the mechanisms that can drive firestorms and provide both warnings and guidance for brands. An OCM typology guides brands’ mitigation strategies.

This paper aims to examine the common roots of both logistics and sustainability phenomena in supply chains to derive a new potential construct, green logistics competency.

Theoretical synthesis and conceptualization of new construct.

Based on Madhavaram and Hunt’s (2008) resource hierarchy concept, the key to successfully competing with a sustainable supply chain may lie in whether the resources enabling both sustainability and effective supply chains are interdependent, as opposed to merely co-existent.

Most current theory regarding sustainable supply chains regards environmentally-friendly factors as resources that are additively bundled with supply chain resources. To determine if competitive performance differentials exist between truly green supply chains, and supply chains that merely adopt green practices, measurement must account for both the interdependence of green and supply chain resources, and their common cultural antecedents.

The study indicates that it is not sufficient for firms to have expertise in both sustainability and in supply chain practices; managers in each of those areas must develop the cultural antecedents of both supply chain and sustainability excellence if firms are to achieve meaningful competitive capabilities through sustainable supply chains.

This conceptual study addresses a paucity of theory describing how and why organizations build a genuinely green supply chain, as opposed to simply adapting supply chains to green practices.

Journals in business logistics, operations management, supply chain management, and business strategy have initiated ongoing calls for Big Data research and its impact on research and practice. Currently, no extant research has defined the concept fully. The purpose of this paper is to develop an industry grounded definition of Big Data by canvassing supply chain managers across six nations. The supply chain setting defines Big Data as inclusive of four dimensions: volume, velocity, variety, and veracity. The study further extracts multiple concepts that are important to the future of supply chain relationship strategy and performance. These outcomes provide a starting point and extend a call for theoretically grounded and paradigm-breaking research on managing business-to-business relationships in the age of Big Data.

A native categories qualitative method commonly employed in sociology allows each executive respondent to provide rich, specific data. This approach reduces interviewer bias while examining 27 companies across six industrialized and industrializing nations. This is the first study in supply chain management and logistics (SCMLs) to use the native category approach.

This study defines Big Data by developing four supporting dimensions that inform and ground future SCMLs research; details ten key success factors/issues; and discusses extensive opportunities for future research.

This study provides a central grounding of the term, dimensions, and issues related to Big Data in supply chain research.

Supply chain managers are provided with a peer-specific definition and unified dimensions of Big Data. The authors detail key success factors for strategic consideration. Finally, this study notes differences in relational priorities concerning these success factors across different markets, and points to future complexity in managing supply chain and logistics relationships.

There is currently no central grounding of the term, dimensions, and issues related to Big Data in supply chain research. For the first time, the authors address subjects related to how supply chain partners employ Big Data across the supply chain, uncover Big Data’s potential to influence supply chain performance, and detail the obstacles to developing Big Data’s potential. In addition, the study introduces the native category qualitative interview approach to SCMLs researchers.

Implementation of supply chain management techniques requires thorough integration of processes between supply chain partners in all functional areas, including sourcing, manufacturing, and distribution. Yet insufficient attention has been given to the means by which firms achieve high levels of integration. This study aims to examine moderators impacting supply chain integration barriers.

Supply chain integration drivers and moderating barriers to supply chain integration were identified by extensive search of the literature, and in‐depth interviews with supply chain managers. A survey was developed to measure levels of supply chain integration drivers, barriers to supply chain integration, and firm performance. The measures were validated using EFA, and the responses analyzed using multiple regression.

The study finds that firms with a desire to improve, operating in a challenging competitive environment typically experience high levels of performance. Further, barriers to supply chain integration can actually increase the firm's ability to achieve firm performance as the firm is required to make greater efforts to overcome those barriers and develop effective supply chain linkages.

This study answers a call for additional research into factors that enable and inhibit supply chain integration, and offers an empirical analysis of the moderating effect of supply chain integration barriers on the relationship between integration drivers and firm performance.

The relationship between supply chain management (SCM) competency and firm performance is not well established empirically. This is largely because proven metrics for quantifying the effects of SCM are scarce. Drawing on the strategic managerial concept of supply chain orientation as a source of competitive advantage, this paper aims to apply three independent sources of secondary data to examine the influence of SCM competency on two important firm performance metrics: customer satisfaction and shareholder value.

SCM competency is assessed with data from the expert opinion element of Gartner Supply Chain Group's (formerly AMR Research) supply chain top 25 rankings; the American Customer Satisfaction Index (ACSI) database and the recently developed Economic Value Added (EVA) Momentum financial metric are utilized as outcome measures.

Firms recognized by peers and experts for superior SCM competency exhibit higher levels of customer satisfaction and shareholder value than their respective industry averages.

Further evidence is required to prove causality does exist between these variables. Limitations associated with the use of secondary data restricted the number of top performer firms available for this analysis. Nevertheless, the strong correlations found between SCM competency and two critical firm performance metrics may help senior managers and managers from other functional areas to better understand potential advantages associated with developing greater SCM competency.

The assessment of two metrics that differentiate top SCM performers from their industry competitors may also help SCM professionals to better convey the impact of SCM competency to non‐supply chain managers and external participants in the supply chain whose support and cooperation are critical to the success of process improvement initiatives.

In addition to the study findings, blending qualitative expert opinion, formal customer satisfaction and quantitative financial performance secondary data represents a relatively novel and informative method that responds to contentions that different approaches should be employed to develop a more holistic understanding of SCM.

The service‐dominant logic (SDL) concept is reshaping the view of business‐to‐business research and practice. Thus, understanding the role of knowledge‐based operant resources, a key component of the SDL paradigm, in the ability of supply chains to shape competitive advantage and performance outcomes is vital. Further, operant resources have a hierarchical structure, with differing effects in building value for a supply chain. This research seeks to explore the effects of different levels of hierarchical operant resources in a retail supply chain setting.

A survey was collected from 300 retailing informants who deal with both key suppliers and customers. The data were examined using hierarchical regression to explore the influence of internal and external operant resources on market performance, subject to the moderating effects of top management support and relationship quality.

There is a positive relationship between internal and external operant resources with market performance outcomes, but those relationships are subject to support from top management toward retailing supply chain relational initiatives. Thus, intangible, dynamic, customer‐oriented resources play an important role in developing retail supply chains’ ability to achieve a market advantage.

This research addresses a need to explore the implications of SDL in a supply chain context by examining the implications of influences of retailer operant resources on the supplier. Further, this research explores the question of operant resources by analysing those resources at various levels within supply chain relationships.