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Managerial attitudes play an important role in facilitating the championship of innovation adop-tion. However, there are few empirical studies which show the mediating role of managerial attitudes as a link between innovation determinants and adoption. Based on innovation theory (Rogers, 1983), we posit a conceptual model to show how managers evaluate internal (relative advantage and compatibility of adopting an innovation) and external (competitive pressure and partner conflict) determinants that affect the intention to adopt technological innovations. We focus on empirical tests conducted on B2C e-commerce. Data collected from 109 differ-ent enterprises indicate that managerial attitudes, through perceived relative advantage and compatibility of adopting a technological innovation, have indirect effects on the intention to adopt the innovation. In addition, competitive pressure has a direct influence on the adoption of an innovation.

PurposeThe purpose of this paper is to examine the problems encountered by clothing merchandisers in managing fabric sample resources, and analyses their expectations of and requirements for a desirable management solution. It then aims to consider the architectural design of an intelligent fabric sample management system prototype, and the development of a construction and implementation plan for a fashion enterprise to install the system.Design/methodology/approachA three‐stage methodological approach is adopted. The first stage is a preliminary study using in‐depth interviews with potential system users; the second involves the architectural design of a five‐component system prototype; and the third develops a multi‐phase construction and implementation plan using a case study.FindingsFour categories of problems in the management of fabric sample resources are identified, the system architecture is designed, and a construction and implementation plan is proposed. Managerial and theoretical implications are also discussed.Practical implicationsThe design process of the research and development (R&D) framework enables fashion enterprises to obtain a deeper understanding of their operations in managing fabric samples and to make wiser decisions in resource allocation. By taking the specific needs of system users into consideration, system solution developers are able to design tailor‐made software packages that are intelligent, user‐friendly and user‐oriented.Originality/valueThrough a logical and systematic process of designing the R&D framework, the paper identifies some "technological rules" which links up the practice of solving an industrial problem with the formulation of substantive theories. This adds to the application of design science research.

Although corporations in the world, especially those in the United States, have spent generously on information technology (IT) and information systems (IS) in recent decades, empirical studies have yielded disappointingly inconsistent findings on the impact of IT investments on firm performance, and the phenomenon of the IT productivity paradox lingers on to this day. A review of the literature on this subject has pointed out several possible reasons underlying such inconsistencies, including data and methodological problems and limitations of research models. Consequently, a process-oriented research model is proposed to mitigate the shortcomings of prior studies. This model incorporates improvements in business process as an independent construct parallel to the capabilities of IT and enterprise systems. Competitive capabilities are included as an intermediate construct to conceptualize the linkage between the independent constructs and the dependent construct of organizational performance. Theories and empirical evidence are drawn from associated management disciplines such as operations management and from a resource-based view of the firm to illustrate and explain that investment in IT and business processes eventually will contribute to organizational performance through the creation and enhancement of competitive capabilities. Finally, the theoretical and managerial implications of this research model are highlighted.

PurposeThis paper examines the relationship between supply chain network structures and firm financial performance and the moderating role of international relations. In this study, which is grounded in social capital theory and applies the perspective of systemic risk, the authors theorize the effects of supply chain network structures on firm performance.Design/methodology/approachThe authors extracted data from two Chinese databases and constructed a supply chain network of the firms concerned based on nearly 4,300 supply chain relations between 2009 and 2018. The authors adopted the fixed effects model to investigate the relationship between supply chain network structures and firm financial performance.FindingsThe econometrics results indicate that network structures, including the degree, centrality, clustering coefficients and structural holes, are significantly related to firm financial performance. A significant and negative relationship exists between international relations and firm financial performance. The authors also find that international relations strongly weaken the relationship between supply chain network structures and firm financial performance.Originality/valueThis study, which collects secondary data from developing countries (e.g. China) and explores the impacts of supply chain network structures on firm stock performance, contributes to the existing literature and provides practical implications.

ABSTRACTAlthough the adoption of service‐dominant logic contributes to the innovativeness of organizations, the relationship between service‐dominant logic and innovation performance has seldom been empirically investigated. To fill this literature gap, this study used relationship learning theory to examine the effects of service‐dominant orientation (SDO), knowledge sharing, and external network on innovation performance through the mediation of relationship learning in technology firms. The proposed model was tested through a field study conducted in Hong Kong Science and Technology Parks Corporation. Data from 82 technology firms were used to test the research model.The results showed that relationship learning mediates the relationships of SDO to innovation performance, knowledge sharing to innovation performance, and external network to innovation performance. The mediation effect confirms that service‐dominant orientated firms have high innovation performance because of the learning from their partner relationships. This research explains that managing the learning from providing services positively influencing innovation of the firm.

Purpose– The purpose of this paper is to investigate if online reviews (e.g. valence and volume), online promotional strategies (e.g. free delivery and discounts) and sentiments from user reviews can help predict product sales.Design/methodology/approach– The authors designed a big data architecture and deployed Node.js agents for scraping theAmazon.compages using asynchronous input/output calls. The completed web crawling and scraping data sets were then preprocessed for sentimental and neural network analysis. The neural network was employed to examine which variables in the study are important predictors of product sales.Findings– This study found that although online reviews, online promotional strategies and online sentiments can all predict product sales, some variables are more important predictors than others. The authors found that the interplay effects of these variables become more important variables than the individual variables themselves. For example, online volume interactions with sentiments and discounts are more important than the individual predictors of discounts, sentiments or online volume.Originality/value– This study designed big data architecture, in combination with sentimental and neural network analysis that can facilitate future business research for predicting product sales in an online environment. This study also employed a predictive analytic approach (e.g. neural network) to examine the variables, and this approach is useful for future data analysis in a big data environment where prediction can have more practical implications than significance testing. This study also examined the interplay between online reviews, sentiments and promotional strategies, which up to now have mostly been examined individually in previous studies.

PurposeAlthough there have been considerable discussions on the business value of adopting blockchain in supply chains, it is unclear whether such blockchain-enabled supply chains (BESCs) can help firms mitigate the negative impact resulting from the recent COVID-19 pandemic. This study aims to answer this important question.Design/methodology/approachThe authors conduct an event study to quantify the financial effects of the COVID-19 pandemic and compare the differences in such effects between treatment firms that have adopted BESCs and matched control firms that have not adopted BESCs. The authors also perform a regression analysis to examine how the role of BESCs in mitigating COVID-19's negative impact varies across firms with different levels of supply chain leanness and complexity. The analysis is based on 88 treatment firms and 88 matched control firms, all of which are publicly listed on the US stock markets.FindingsThe test results suggest that although both the treatment and control firms are negatively affected by the COVID-19 pandemic, the effect is less negative for the treatment firms compared to the control firms, demonstrating the role of BESCs in mitigating the negative impact caused by the COVID-19 pandemic. Moreover, the mitigating role of BESCs is more pronounced for firms with lean and complex supply chains.Originality/valueThis study is among the first to provide empirical evidence on the mitigating role of BESCs during the COVID-19 pandemic, highlighting the importance of adopting blockchain in supply chains with high uncertainties and disruption risks.