Do Companies Adopt Big Data as Determinants of Sustainability: Evidence from Manufacturing Companies in Jordan

Information and communication technology make it easier for managers to gather customer data quickly and efficiently. However, managing, analysing, and utilizing the vast amount of data for sustainability decision are not easy. Therefore, this study aims to examine the readiness of manufacturing firms in adopting big data analytics in sustainable development. Moreover, this study employed the Partial Least Square Structural Equation Modelling (PLS-SEM) technique and analyses the data collected from 172 respondents working in different organizations in Amman and Jordan. The results reveal that there is a significant relationship between top management support and competitive pressures and intentions to adopt big data analytics. However, the moderating influence of perceived risk on the relationship between intention and actual use of big data has not been proved. The study provides fresh findings on determinants of intention to adopt big data analytics, actual use, and moderating role of perceived risk within the model to develop sustainability. Furthermore, the study has a number of theoretical and practical implications. Our main findings provide a deeper understanding of the enablers of BDA adoption through the development of a framework that includes direct and moderating constructs, as well as recommendations to practitioners on how to enhance BDA adoption based on eight BDA enablers

A deep learning model for behavioural credit scoring in banks

The main aim of this paper is to help bank management in scoring credit card clients using machine learning by modelling and predicting the consumer behaviour concerning three aspects: the probability of single and consecutive missed payments for credit card customers, the purchasing behaviour of customers, and grouping customers based on a mathematical expectation of loss. Two models are developed: the first provides the probability of a missed payment during the next month for each customer, which is described as Missed payment prediction Long Short Term Memory model (MP-LSTM), whilst the second estimates the total monthly amount of purchases, which is defined as Purchase Estimation Prediction Long Short Term Memory model (PE-LSTM). Based on both models, a customer behavioural grouping is provided, which can be helpful for the bank’s decision-making. Both models are trained on real credit card transactional datasets. Customer behavioural scores are analysed using classical performance evaluation measures. Calibration analysis of MP-LSTM scores showed that they could be considered as probabilities of missed payments. Obtained purchase estimations were analysed using mean square error and absolute error. The MP-LSTM model was compared to four traditional well-known machine learning algorithms. Experimental results show that, compared with conventional methods based on feature extraction, the consumer credit scoring method based on the MP-LSTM neural network has significantly improved consumer credit scoring

Understanding retail supply chain during COVID-19: A systematic review

Purpose– The aim of this paper is to identify the themes that emerged from retail supply chain (RSC) literature during the COVID-19 pandemic that inform future mitigation and recovery strategies. Design/methodology/approach– This study analyses contributions in the RSC literature using four databases: Emerald, Elsevier (Science Direct), Wiley, and Taylor & Francis. The systematic review approach resulted in identifying 74 articles covering 2020 to 2022. Findings– Four themes emerged from RSC literature on COVID-19. The first theme highlighted factors that exacerbated the effects of COVID-19 pandemic on the RSC. The second theme focused on the types of disruptions that occurred in the RSC during the pandemic. The third theme demonstrated the recovery strategies used to reduce the impact of COVID-19 on the RSC. The fourth theme identified proposed mitigation strategies for the RSC post COVID-19 outbreak. Practical implications–The study provides a deeper understanding of how retail supply chain managers could successfully reduce the effects of the COVID-19 pandemic by dealing with interruptions. Based on the reviewed studies and the four themes that evolved from RSC literature on COVID-19 throughout 2020-2022, eleven key RSC strategies and lessons have been recommended to decision makers in the retail industry. Originality/value– This is the first study to identify the themes that emerged from RSC literature during the COVID-19 pandemic to inform future mitigation and recovery strategies. The resulting themes add to the existing body of knowledge and established the need for further research into other sectors that might be affected by future pandemics. Keywords: Retail Supply Chain, Supply Chain Disruptions, Mitigation Strategies, Recovery Strategies, Covid-19, Systematic Review

A Relationship between Supply Chain Practices, Environmental Sustainability and Financial Performance: Evidence from Manufacturing Companies in Jordan

Pursuing sustainable development creates competitiveness for manufacturing firms in the market, however the financial pressure of adopting sustainable environmental practices is still a major concern. Few studies were found on the inter-relationships between supply chain management practices, environmental sustainability, and firm financial performance. Moreover, manufacturing companies are compelled by different pressure groups across the globe to maintain environmental standards while conducting their business and supply chain activities. Therefore, the current study aims to investigate the impact of supply chain practices on environmental sustainability and financial performance. In addition, the role of environmental sustainability as a mediator between supply chain management and financial performance was analyzed to improve sustainable development. A well-designed questionnaire was administered to manufacturing companies in Jordan for data collection. A total of 376 responses were analyzed and the proposed hypotheses were tested by using Structural Equation Modelling (SEM) approach. The results reveal that environmental sustainability was tested significantly and influenced by supply chain practices such as relationship with customers, postponement, level of information sharing, and information quality. Whereas environmental sustainability had a significant direct effect on financial performance. Finally, environmental sustainability mediated the relationship of all supply chain management practices with financial performance except strategic supplier partnership dimension. The study provides policy guidelines to decision makers while simultaneously assists the managers to improve sustainability practices in manufacturing companies

Identifying and Categorizing Sustainable Supply Chain Practices Based on Triple Bottom Line Dimensions: Evaluation of Practice Implementation in the Cement Industry

Recent research has placed greater emphasis on sustainable supply chain management (SSCM), specifically within the manufacturing sector. SSCM expands upon traditional supply chain management (SCM) by taking environmental and social considerations into account. Given the sustainability challenges facing the cement industry, SSCM has become a crucial topic for companies operating in this sector. Accordingly, the aim of this study is to identify and categorize SSCM practices based on the triple bottom line (TBL) dimensions of sustainability. Additionally, the study assesses the adoption of SSCM practices by Jordanian cement manufacturers according to the developed model. There is a lack of studies focused on creating a tailored and comprehensive SSCM conceptual model to evaluate sustainability practices within cement manufacturing. Therefore, this study attempted to develop a model for SSCM practices by incorporating 23 SSCM factors divided into three dimensions of sustainability: nine factors of environmental SSCM, seven factors of social SSCM, and seven factors of economic SSCM. The study employed a quantitative research approach, using a structured questionnaire to collect data from 41 cement company managers in Jordan and industry specialists. The proposed hypotheses were tested using SPSS software. The research findings revealed that the average level of implementation for all environmental factors was at a medium level within the Jordanian cement industry, the average level of implementation for all social factors was at a high level, and the average level of implementation for all economic factors was at a medium level. Overall, the implementation of SSCM practices was found to be at a moderate level. The study also provided a detailed level of implementation for each SSCM practice for each dimension of sustainability. By identifying and categorizing SSCM practices related to the cement industry, this study addresses a gap in the literature. It also highlights critical sustainability issues for decision-makers and academics, which can aid in the evaluation and improvement of SSCM practices in the cement industry. Future studies should aim to replicate this study with larger sample sizes and probability-sampling techniques to enhance the generalizability of the results

Exploring the influence of lean manufacturing and total quality management practices on environmental sustainability: the moderating role of quality culture

Purpose: Organizations have released the importance of lean manufacturing practices (LMPs) and total quality management (TQM) in enhancing competitiveness. However, the implementation of LMPs and TQM becomes more complex when discerning the environmental sustainability position. The complexity stems from the fact that LMPs and TQM are more intricate because of cultural differences. Thus, this study aims to tackle the aforementioned phenomenon by investigating the impact of LMPs and TQM on environmental sustainability moderated by quality culture. Design/methodology/approach: A survey was distributed among small and medium enterprises (SMEs) in Jordan; thus, 315 valid responses were received. Partial least square structural equation modelling was used to analyze the data and test hypotheses. Findings: The findings showed that environmental sustainability was significantly impacted by all the LMP practices except Kanban and all the TQM practices except statistical process control. Moreover, quality culture significantly and negatively moderated the relationship between TQM and environmental sustainability. However, the influence of LMPs on environmental sustainability was not significantly moderated by quality culture. Practical implications: This study has implications for policymakers in SMEs, supply chain managers and academics regarding the importance of LMPs and TQM systems for implementing environmental sustainability and the role of quality culture. Social implications: This study provides guidelines for decision-makers on the pathways that enable them to sustain the environment to safeguard the natural ecosystem and natural resources for upcoming generations. Originality/value: The originality of this study stems from the alignment of LMPs and TQM in enhancing environmental sustainability, taking into consideration the role of quality culture in SMEs, where previous studies failed short to investigate this phenomenon