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Research on information technology adoption increasingly focuses on the interactive and temporal aspects of this process. This paper addresses the research gaps in information technology adoption process by which small agri-businesses bond in to a managed supply chain and with their social network. We draw on theories of social institutional isomorphism, organizational culture, and diffusion of innovation as a basis to hypothesize on the inter- and intra-organizational process relevant to information technology adoption. The small agricultural businesses engaged in food traceability technology in Taiwan serve as a sample for this study. A total of 81 valid responses of small agriculture business are obtained for data analysis, using partial least square methods. Our findings show that rather than focus on the adoption attributes of relative advantage and complexity small business are socialized by their network, in a way that instructs their business process. For small business, therefore, technology adoption is a question of maintaining a social identity within the supply chain.

How to develop a better patient safety culture has been an important goal for healthcare organizations, but the effects of safety culture on psychosocial factors, such as emotional exhaustion and stress, have not been fully addressed. This study aimed to reconfigure important dimensions affecting safety culture and examine the associations between safety culture and psychosocial factors (emotional exhaustion and work-life balance). The partial least squaring technique was used to analyze the data, showing that job satisfaction (β = 0.320, P < 0.001), working conditions (β = 0.307, P < 0.001), and perception of management (β = 0.282, P < 0.001) positively affected the safety climate. The safety climate and work-life balance could reduce the occurrence of emotional exhaustion, whereas a high-stress environment would cause a higher level of emotional exhaustion. Given these findings, hospitals should endeavor to help employees feel safe and not threatened, reduce stress, and advise them to maintain a good work-life balance.

Going beyond the traditional business to consumer air transport passenger perspective, this paper examines what we can learn from combining transaction marketing (TM) and relationship marketing (RM) orientations in respect to customer loyalty in the context of business to business (B2B) freight transportation markets. We model and examine post-transactional air freight express (integrator) customer behavior of 170 manufacturing companies and our results suggest that both TM and RM orientations influence customer loyalty as TM has a positive direct and indirect impact on loyalty due an mediating effect on RM outweighing potential dark side effects of RM on customer loyalty. This indicates that transaction-based marketing can support a relationship structure with the aim to nurture customer loyalty in B2B freight markets. In contrast to theoretical notions and contradictions between simultaneous competition/cooperation and interdependence/dependence of customers and service providers, we show that managers of freight and logistics companies should embrace the coexistence of TM and RM approaches and develop strategies that value long-standing transactional customers as they provide opportunities to create effective customized solutions.

Crossdocks play an important role in supply chain operations. Due to the need to decrease transportation lead time to coordinate with other supply chain activities such as just-in-time, make-to-order, or merge-in-transit strategies, shortening the total transfer time at crossdocks is increasingly important. In this research, we use real-time information about freight transferring within a crossdock to schedule waiting inbound trailers in order to reduce the time freight spends in a crossdock. We use dynamic simulation models to compare the performance of several strategies. These are first-come, first-served, look-ahead, minimum processing time, and minimum total time policies. We examine these under different trailer arrival headways, crossdock layouts, and destination distributions. Our simulation results show that our time-based algorithms save more time than the first-come, first-served and look-ahead policies. In addition, these algorithms appear to result in higher service reliability and productivity.

Some customers might have negative behavior that harms a company’s benefit. In this study, we emphasize on incorporating negative behavior incurred by these customers into the calculation of customer lifetime value (CLV) when doing business with them. Data from a railway e-booking system was adopted for a case study. The invisible cost of cancellation was incorporated along with the revenue of ticket selling into the calculation of CLV. From the results, we conclude that our model has a good estimation about the customers’ real values and can cherry-pick out customers with higher values than the traditional CLV models. By cherry-picking customers, lower cancellation rate and higher customer satisfaction are expected.