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Drawing on dynamic capability theory, this study investigates how online–offline channel integration (OOCI) affects a firm's supply chain resilience and how such an effect is moderated by market turbulence and regulatory uncertainty.

A sample of 273 Chinese firms that conduct online and offline business and hierarchical regression analysis were used to examine the research model.

The results suggest that the effect of OOCI on supply chain resilience differs in terms of its dimensions (i.e. information integration, transaction integration and service integration). While information integration and service integration were positively associated with supply chain resilience, transaction integration had a non-significant relationship with supply chain resilience. Moreover, market turbulence negatively moderated the effect of transaction integration and positively moderated the effect of service integration. Regulatory uncertainty positively moderated the effect of transaction integration and negatively moderated the effect of service integration. Implications and suggestions for future research are discussed.

This study examines the effect of OOCI on supply chain resilience. It further explores the influence of market turbulence and regulatory uncertainty on the relationship between OOCI and supply chain resilience.

Understanding customer behavior from the perspective of channel integration has become a major stream of research in multi-channel retailing literature. Yet, despite recent advancements in scholarship, how retailers can most effectively sustain customers in online retailing remains unclear. Scholars have suggested online–offline channel integration (OOCI) as an effective multi-channel approach for increasing online loyalty; yet, few studies have explored OOCI's influencing mechanism. This study addresses that gap by investigating how OOCI helps achieve customer loyalty online and further examines the moderating role of retailer credibility in the influencing mechanism of OOCI.

The research model driving this study draws upon the stimulus-organism-response (S-O-R) model and cue consistency theory. The authors collected a sample of 259 customers in China with experience making multi-channel purchases from retailers that have implemented OOCI in online retailing. Structural equation modeling and response surface analyses were employed to conduct data analysis.

The results revealed that the relationship between OOCI and customers' online channel loyalty was mediated by customers' perceptions of the usefulness and risks of online channel usage. The results also found that congruence and incongruence between informational OOCI (IOOCI) and fulfillment OOCI (FOOCI) had different curvilinear associations with perceived online channel usefulness and perceived online channel risk. In addition, retailer credibility weakened the effects of IOOCI on perceived online channel usefulness and FOOCI on perceived online channel risk but strengthened the effect of IOOCI on perceived online channel risk and had no impact on the effect of FOOCI on perceived online channel risk.

Theoretical and practical implications of this study are also discussed.

In order to accomplish the goals of maintaining an effective supply chain, the firm needs to establish and maintain long-term relationships with its suppliers. Most supply chain problems inherently involve multiple conflicting criteria. Risks in the supply chain are dynamic in nature. While some risks can be either reduced or eliminated, new ones will appear.

This chapter will focus on the development of a mufti-criteria model using meta-goal programming to develop a supplier selection process. The goals of the model include (1) the minimization of the net cost for all items, (2) the minimization of the defective items, and (3) the minimization of late-delivered items.

The purpose of this study is to examine the underlying mechanisms of exploitative innovation and exploratory innovation between social media usage and organizational agility, and elucidate the moderating role of learning goal orientation (LGO) in the above relationships, based on adaptive structuration theory (AST).

Based on a multiple-respondent matched survey of 334 Chinese e-commerce firms, authors employed structural equation modeling to examine the correlations among social media usage, exploitative innovation, exploratory innovation and organizational agility. Hierarchical regression analysis was used to examine the moderating role of LGO.

This study's empirical findings demonstrate that exploitative innovation and exploratory innovation mediate the relationship between social media usage and organizational agility in different ways. Further, LGO positively moderates the relationship between social media usage for customer acquisition and exploratory innovation, as well as the relationship between social media usage for customer relationship and exploitative innovation.

Firms are advised to leverage different types of social media usage to facilitate exploitative innovation and exploratory innovation and promote organizational agility. In addition, LGO within a firm should be established to enhance the effects of social media usage on exploitative innovation and exploratory innovation.

This study adds to the literature on social media usage by proposing and examining exploitative innovation and exploratory innovation as explanatory mechanisms to facilitate organizational agility. This study further identifies LGO as a boundary condition of social media usage's effect on exploitative innovation and exploratory innovation. By contextualizing social media as advanced information technology, this study contributes to the contextualization of AST in the social media context.

Using dynamic capability theory, this study investigates how information technology (IT) support affects firms' online and offline cross-channel integration (CCI). In addition, it applies institutional theory to examine how the relationships between IT support and CCI are moderated by firms' institutional environments.

A sample of 308 firms in China that conduct business in online and offline channels was empirically tested through hierarchical regression analysis.

The results showed two types of IT support facilitated CCI: IT support for strategy and IT support for process. The relationship between IT support for process and CCI was stronger than that between IT support for strategy and CCI. The results further indicated institutional environment (i.e. dysfunctional competition and government support) played differing roles in these effects, such that the relationship between IT support for strategy and CCI was significantly weakened by dysfunctional competition yet enhanced by government support. However, neither dysfunctional competition nor government support had a significant moderating role in the relationship between IT support for process and CCI.

This study identifies different IT support types as antecedents of CCI. It is also one of the earliest attempts to explore the influence of institutional environment on the relationship between IT support and CCI.

The investigation of organization's ambidextrous innovation is a challenge in the research studies of management sciences. As existent literature showed a positive relation between dynamic capability (DC) and innovation, few empirical studies are conducted to explain how DC impacts on the balanced and combined dimension of ambidexterity and still less on how social network moderates this relation. As a result, this paper aims to investigate and provide empirical evidence on DC’s influence on ambidexterity in the context of China.

By a relational model of DC, ambidextrous innovation and social network, this study has conducted multiple regression analysis on the data collected from 350 small and medium enterprises (SMEs) in mainland China.

The results show that, DC has positive influence on both the combined and balanced dimension of ambidexterity; and both the relational network and structural network play an inverted U moderating role, where the moderation of relational network is stronger than that of structural network.

This study provides empirical support on DC's influence on ambidexterity together with the moderation of social network.

Purpose: Risk is a multifaceted concept, and its identification requires complex approaches that are often misunderstood. The consequence is that decisions are based on limited perception rather than the full value and meaning of what risk is, as a result, the way it is being tackled is incorrect. The individuals are often limited in their perceptions and ideas and do not embrace the full multifaceted nature of risk. Regulators and individuals want to follow norms and checklists or overuse models, simulations, and templates, thereby reducing responsibility for decision-making. At the same time, the wider use of technology and rules reduces the critical thinking of individuals. We advance the automation process by building robots that follow protocols and forget about the part of risk assessment that cannot be programed. Therefore, with this study, the objective of this study was to discover how people define risk, the influencing factors of risk perception and how they behave toward this perception. The authors also determine how the perception differed with age, gender, marital status, education level and region. The novelty of the research is related to individual risk perception during COVID-19, as this is a new and unknown phenomenon. Methodology: The research is based on the analysis of the self-administered purposely designed questionnaires we distributed across different social media platforms between February and June 2020 in Europe and in some cases was carried out as a interview over communication platforms such as “Skype,” “Zoom” and “Microsoft Teams.” The questionnaire was divided into four parts: Section 1 was designed to collect demographic information from the participants; Section 2 included risk definition statements obtained from literature and a preliminary discussion with peers; Section 3 included risk behavior statements; and Section 4 included statements on risk perception experiences. A five-point Likert Scale was provided, and participants were required to answer along a scale of “1” for “Strongly Agree” to “5” for “Strongly Disagree.” Participants also had the option to elaborate further and provide additional comments in an open-ended box provided at the end of the section. 466 valid responses were received. Thematic analysis was carried out to analyze the interviews and the open-ended questions, while the questionnaire responses were analyzed using various quantitative methods on IBM SPSS (version 23). Findings: The results of the analysis indicate that individuals evaluate the risk before making a decision and view risk as both a loss and opportunity. The study identifies nine factors influencing risk perception. Nevertheless, it must be emphasized that we can continue to develop models and rules, but as long as the risk is not understood, we will never achieve anything.

In seminal work, Den Haan et al. (2007, 2010, 2011) show business loans respond in the opposite direction of what may be intended by monetary policy action in the United States and Canada. Based on various approaches, identification schemes, and samples, we document evidence this loan puzzle is not exclusive to developed economies but is also pervasive in emerging markets. We find business loans generally decline following expansionary monetary policy shocks. A preponderance of statistical and structural evidence indicates important transmissions of this puzzle from the United States to emerging markets.

Recent U.S. Treasury yields have been constrained to some extent by the zero lower bound (ZLB) on nominal interest rates. Therefore, we compare the performance of a standard affine Gaussian dynamic term structure model (DTSM), which ignores the ZLB, to a shadow-rate DTSM, which respects the ZLB. Near the ZLB, we find notable declines in the forecast accuracy of the standard model, while the shadow-rate model forecasts well. However, 10-year yield term premiums are broadly similar across the two models. Finally, in applying the shadow-rate model, we find no gain from estimating a slightly positive lower bound on U.S. yields.

This chapter studies the dynamic responses of the conditional quantiles and their applications in macroeconomics and finance. The authors build a multi-equation autoregressive conditional quantile model and propose a new construction of quantile impulse response functions (QIRFs). The tool set of QIRFs provides detailed distributional evolution of an outcome variable to economic shocks. The authors show the left tail of economic activity is the most responsive to monetary policy and financial shocks. The impacts of the shocks on Growth-at-Risk (the 5% quantile of economic activity) during the Global Financial Crisis are assessed. The authors also examine how the economy responds to a hypothetical financial distress scenario.