• The effect of buyers’ socialization efforts on the culture of their key strategic supplier and its impact on supplier operational performance

      Cadden, Trevor; Cao, Guangming; Yang, Ying; McKittrick, Alan; McIvor, Ronan; Onofrei, George (Taylor and Francis Ltd., 2020-07-30)
      This paper investigates if inter-organizational socialization mechanisms initiated by a buyer organization towards a strategic supplier can influence the culture within that supplier organization to ultimately improve supplier performance to the buyer. Using a quantitative sample of 279 UK companies from across a variety of industry sectors, statistical techniques were utilized to examine the effect of informal and formal socialization mechanisms on the culture of a strategic supplier as measured by their organizational practices and the subsequent supplier performance outcomes. It was found that both informal and formal socialization efforts by a buyer organization have a significant influence on the culture of the supplier organization as measured by their organizational practices. Socialization efforts by the buyer organization influence the organizational practices of the supplier to be more result-oriented, employee-centred, open, pragmatic to customer needs and market focussed. These organizational practices were found to positively influence supplier operational performance in the eyes of the buyer organization as measured by on time delivery, conformance to product specifications, flexibility to respond to changing customer needs and cost reduction initiatives. Modelling the influence of informal and formal socialization efforts by a buyer on the organizational culture of a key supply chain partner provides new insights to academics. Firstly, this work makes a significant contribution to the extant research on socialization in the supply chain literature. Secondly, it raises the importance of understanding the influence of culture on supplier operational performance. Although the study used a dyadic method to validate the cultural insights, our study only took a snapshot of culture at one point in time. Organization culture as displayed through organizational practices is a complex construct that changes over time. Therefore, to further understand the intricacies of organization culture, a longitudinal study would be useful in the future. Secondly, future studies could develop into themes such as the green supply chain and sustainability issues. Finally, our study was undertaken in the UK. It would be useful to replicate this study in a different setting, including Eastern countries. Organizations should engage early with their key supply base from a socialization perspective. The importance of joint away days, cross function teams alongside effective communication and on site visits have been fund to have a significant influence on shaping a high performance culture along the supply chain. Therefore, a buyers’ early understanding of their key supplier’s culture via these mechanisms appear critical for long-term supply chain success. Measuring supplier culture at the visible level of organizational practices removes the ethereal qualities often attributed to culture as a concept; buyers can influence supplier culture. This paper presents an empirically tested model which includes informal socialization, formal socialization, deconstructed organizational culture and supplier operational performance in a supply chain setting.
    • Green supply chain management – food for thought?

      Ali, Abdul; Bentley, Yongmei; Cao, Guangming; Habib, Farooq; University of Bedfordshire (Taylor and Francis Ltd., 2016-09-13)
      This paper investigates the impact of green supply chain management (GSCM) practices on the performance of UK food retail small and medium-sized enterprises (SMEs). A quantitative approach using a non-probability sampling of 84 participants was employed. Based on the literature review, five hypotheses were developed and tested using the partial least square-structural equation modeling (SEM-Smart PLS 2.03) approach. The reviewed literature revealed that key internal drivers (ID) and external pressures (EP) stimulate organizations to initiate GSCM practices in UK food retail SMEs. Though empirical findings strongly supported the statement that ID influence GSCM practices, they did not show a significant relationship between EP and GSCM practices. Literature also suggests that practicing GSCM can help improve the efficiency, brand image (BI) and profitability, and thus improve the overall firm performance which is also empirically proved. This study helps enrich existing theories on SCM and organizational performance. As to practical impact, this study should facilitate SMEs in GSCM practices and thus help green the economy. While the findings of this study have limited generalisability as the data were collected from UK SMEs only and the sample size was comparatively small, this research establishes a foundation for further study in this domain.
    • Impact of engaging teaching model (ETM) on students’ attendance

      Bukoye, Oyegoke Teslim; Shegunshi, Anjali; University of Bedfordshire (Taylor and Francis Ltd., 2016-08-24)
      Non-attendance in Higher Education is not a new concept. In recent years with the exponential growth in digital learning, physical attendance has become a more complex issue. Educators are continually advocating an engaging teaching approach for students as a means of enhancing learning. This on-going study focuses on exploring the existing issues related to student non-attendance and the impact of a proposed engaging teaching model (ETM) on students’ attendance. This research questions whether an engaged learning session could make a positive impact on students’ attendance. The objectives highlighted in this study are to examine the reasons for non-attendance and generic measures for increasing attendance; and highlight the impact of an engaging teaching model on students’ attendance. The inference drawn from the qualitative method undertaken by 89 participants is the development of ETM to enhance students’ attendance. The study is beneficial to educators, researchers and policy-makers, in order for them to consider not only the content of their subjects, but also how students engage with these resources, which consequently facilitate students’ interest in attending lectures.
    • The mediating effect of environmental and ethical behaviour on supply chain partnership decisions and management appreciation of supplier partnership risks

      Gallear, David; Ghobadian, Abby; He, Qile; Brunel University; University of Reading; University of Bedfordshire (Taylor and Francis Ltd., 2014-07-18)
      Green supply chain management and environmental and ethical behaviour (EEB), a major component of corporate responsibility (CR), are rapidly developing fields in research and practice. The influence and effect of EEB at the functional level, however, is under-researched. Similarly, the management of risk in the supply chain has become a practical concern for many firms. It is important that managers have a good understanding of the risks associated with supplier partnerships. This paper examines the effect of firms investment in EEB as part of corporate social responsibility in mediating the relationship between supply chain partnership (SCP) and management appreciation of the risk of partnering. We hypothesise that simply entering into a SCP does not facilitate an appreciation of the risk of partnering and may even hamper such awareness. However, such an appreciation of the risk is facilitated through CRs environmental and stakeholder management ethos. The study contributes further by separating risk into distinct relational and performance components. The results of a firm-level survey confirm the mediation effect, highlighting the value to supply chain strategy and design of investing in EEB on three fronts: building internal awareness, monitoring and sharing best practice.
    • Optimising online review inspired product attribute classification using the self-learning particle swarm-based Bayesian learning approach

      Maiyar, Lohithaksha M.; Cho, SangJe; Tiwari, Manoj Kumar; Thoben, Klaus-Dieter; Kiritsis, Dimitris (Taylor and Francis Ltd., 2018-10-24)
      Bowing to the burgeoning needs of online consumers, exploitation of social media content for extrapolating buyer-centric information is gaining increasing attention of researchers and practitioners from service science, data analytics, machine learning and associated domains. The current paper aims to identify the structural relationship between product attributes and subsequently prioritise customer preferences with respect to these attributes while exploiting textual social media data derived from fashion blogs in Germany. A Bayesian Network Structure Learning model with the K2score maximisation objective is formulated and solved. A self-tailored metaheuristic approach that combines self-learning particle swarm optimisation (SLPSO) with the K2 algorithm (SLPSOK2) is employed to decipher the highest scored structures. The proposed approach is implemented on small, medium and large size instances consisting of 9 fashion attributes and 18 problem sets. The results obtained by SLPSOK2 are compared with the particle swarm optimisation/K2score, Genetic Algorithm/K2 score and ant colony optimisation/K2 score. Results verify that SLPSOK2 outperforms its hybrid counterparts for the tested cases in terms of computational time and solution quality. Furthermore, the study reveals that psychological satisfaction, historical revival, seasonal information and facts and figure-based reviews are major components of information in fashion blogs that influence the customers.
    • Part segregation based on particle swarm optimisation for assembly design in additive manufacturing

      Maiyar, Lohithaksha M.; Singh, Sube; Prabhu, Vittal; Tiwari, Manoj Kumar (Taylor and Francis Ltd., 2019-05-05)
      Minimising total production time in the additive or layered manufacturing is a critical concern, and in this respect, the idea of balancing assembly time and build time is rapidly gaining research attention. The proposed work intends to provide benefit in terms of reduced lead time to customers in a collaborative environment with simultaneous part printing. This paper formulates a mixed-integer non-linear programming (MINLP) model to evaluate the near optimal threshold area and support material allocation while segregating parts for a single material additive manufacturing set-up. The resulting time minimisation model is finitely bounded with respect to support material volume, total production time and total assembly cost constraints. A novel swarm intelligence-based part segregation procedure is proposed to determine the number of part assemblies and part division scheme that adheres to cross-sectional shape, cross-sectional area, and height restrictions. The proposed approach is illustrated and evaluated for objects with regular as well as free-form surfaces using two different hypothetically simulated real size 3D models. Results indicate that the proposed approach is able to reduce the total amount of manufacturing time in comparison with single part build time for all the tested cases.
    • Robust optimisation of sustainable food grain transportation with uncertain supply and intentional disruptions

      Maiyar, Lohithaksha M.; Thakkar, Jitesh J. (Taylor and Francis Ltd., 2019-09-09)
      The proliferating need for sustainability intervention in food grain transportation planning is anchoring the attention of researchers in the interests of stakeholders and environment at large. Uncertainty associated with food grain supply further intensifies the problem steering the need for designing robust, cost-efficient and sustainable models. In line with this, this paper aims to develop a robust and sustainable intermodal transportation model to facilitate single type of food grain commodity shipments while considering procurement uncertainty, greenhouse gas emissions, and intentional hub disruption. The problem is designed as a mixed integer non-linear robust optimisation model on a hub and spoke network for evaluating near optimal shipment quantity, route selection and hub location decisions. The robust optimisation approach considers minimisation of total relative regret associated with total cost subject to several real-time constraints. A version of Particle Swarm Optimisation with Differential Evolution is proposed to tackle the resulting NP-hard problem. The model is tested with two other state-of the art meta-heuristics for small, medium, and large datasets subject to different procurement scenarios inspired from real time food grain operations in Indian context. Finally, the solution is evaluated with respect to total cost, model and solution robustness for all instances.