No abstract

The Cold Supply Chain (CSC) is an integral part of the supply chain of perishable products. The aim of this research is to examine the inhibitors that have a major impact on the performance of CSC operations in the United Arab Emirates (UAE). This study provides a synthesis and suggests a hierarchical model among CSC inhibitors and their respective relevance. The hierarchical synthesis of twelve (12) primary CSC inhibitors is achieved through a comprehensive literature review and consultation with academics and CSC professionals. This study used semi-structured interviews, a fuzzy interpretive structural modeling (FISM) and a Fuzzy-MICMAC (FMICMAC) analysis to explore and establish the relationship between and among identified inhibitors. FISM is used to examine the interaction between inhibitors, while FMICMAC analysis is used to examine the nature of inhibitors on the basis of their dependence and driving power. The results of the FISM and FMICMAC analysis show the inter-relationships and relative dominance of identified inhibitors. The results show that some inhibitors are of high strategic importance due to their high driving power and low dependence. These inhibitors seek more management attention in order to improve their effectiveness. The result of a hierarchical model helps to understand the influence of a particular inhibitor on others. ‘Higher capital and operating costs’ occupy the highest level in the FISM model. The ‘fragmented cold supply chains’, ‘lack of skilled labor’, ‘inadequate information system infrastructure’ and ‘lack of commitment by top level management’ had strong driving power but weak dependence, which characterizes them as independent inhibitors. Management should be extra careful when dealing with these inhibitors as they influence the effects of other variables at the top of the FISM hierarchy in the overall management of the cold supply chain. The study also suggests a number of recommendations for addressing these inhibitors in cold supply chains operating in the UAE. With due attention and care for these inhibitors, the operation of the cold supply chains is likely to be even more successful.

Open Data initiative is attracting considerable interest globally due to the growing phenomena of transparency, accountability, quality of life, and business. The adoption of open data technologies is inevitably an issue to better exploit the full potential and benefits of open data available to the public. The main issue in our knowledge of open data technologies is the scarcity of research studies on the adoption of open data technologies. Thus, the main objective of this study is to predict and explain the factors that influence the adoption of open data technologies. A Unified Model of Electronic Government Adoption (UMEGA) was employed as a lens to examine the influencing factors including additional factors i.e. imitating the behavior of others, disregarding own beliefs, and grievance redressal to make a novel contribution in the adoption studies. The survey method was used to collect the data from citizens and analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) technique in SmartPLS 3. Satisfactory results are obtained proving that facilitating conditions has a significant positive influence on effort expectancy, effort expectancy on performance expectancy, performance expectancy on attitude, and attitude on behavioral intention to adopt open data technologies even though the number of participants is very small. Implications for the academics and managers are also outlined. Future researchers should find more concrete pieces of evidence upon collecting a large number of responses.