Partial least squares structural equation modeling (PLS-SEM) has become popular in the information systems (IS) field for modeling structural relationships between latent variables as measured by manifest variables. However, while researchers using PLS-SEM routinely stress the causal-predictive nature of their analyses, the model evaluation assessment relies exclusively on criteria designed to assess the path model's explanatory power. To take full advantage of the purpose of causal prediction in PLS-SEM, it is imperative for researchers to comprehend the efficacy of various quality criteria, such as traditional PLS-SEM criteria, model fit, PLSpredict, cross-validated predictive ability test (CVPAT) and model selection criteria.,A systematic review was conducted to understand empirical studies employing the use of the causal prediction criteria available for PLS-SEM in the database of Industrial Management and Data Systems (IMDS) and Management Information Systems Quarterly (MISQ). Furthermore, this study discusses the details of each of the procedures for the causal prediction criteria available for PLS-SEM, as well as how these criteria should be interpreted. While the focus of the paper is on demystifying the role of causal prediction modeling in PLS-SEM, the overarching aim is to compare the performance of different quality criteria and to select the appropriate causal-predictive model from a cohort of competing models in the IS field.,The study found that the traditional PLS-SEM criteria (goodness of fit (GoF) by Tenenhaus, R2 and Q2) and model fit have difficulty determining the appropriate causal-predictive model. In contrast, PLSpredict, CVPAT and model selection criteria (i.e. Bayesian information criterion (BIC), BIC weight, Geweke–Meese criterion (GM), GM weight, HQ and HQC) were found to outperform the traditional criteria in determining the appropriate causal-predictive model, because these criteria provided both in-sample and out-of-sample predictions in PLS-SEM.,This research substantiates the use of the PLSpredict, CVPAT and the model selection criteria (i.e. BIC, BIC weight, GM, GM weight, HQ and HQC). It provides IS researchers and practitioners with the knowledge they need to properly assess, report on and interpret PLS-SEM results when the goal is only causal prediction, thereby contributing to safeguarding the goal of using PLS-SEM in IS studies.

Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research

https://bura.brunel.ac.uk/bitstream/2438/17809/2/FullText.pdf

Forecasting SMEs' credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach

This paper presents the concerns in agri-food supply chain. Further the research investigates the role of information and communication technology (ICT) in agri-food supply chain and determines the impact of supply chain management (SCM) practices on firm performance.,The theoretical framework was proposed for the study on the basis of existing literature. Data for the study was collected with the help of structured questionnaire from 121 executives and officers of the public food distribution agency. Partial least square (PLS)–structured equation modeling was employed to test the framework and hypotheses.,The results indicate that ICT and SCM practices (logistics integration and supplier relationships) have a significant relationship. Furthermore, SCM practices (information sharing, supplier relationship and logistics integration) have a significant and positive impact on performance of the organization.,Further research could be carried out to test the moderation effect of SCM practices between ICT and organizational performance (OP). Extending the research study to the companies operating in other sectors can enhance the external validity of the study and improve the accuracy of parameters examined.,This study can be of interest to the agri-food industry as well as other industry practitioners interested in improving the performance of the organization from the view of supply chain.,The outcomes of this study have important implications that translate into a series of recommendations for the management of public food distribution as well as other agri-food-based supply chains.

Exploring the relationship between ICT, SCM practices and organizational performance in agri-food supply chain

The effect of supply chain quality management practices and capabilities on operational and innovation performance: Evidence from Chinese manufacturers

Exploring the relationship between mechanisms, actors and instruments in supply chain finance: A systematic literature review

– The purpose of this paper is to examine the effect of small and medium enterprises (SMEs)’ supply chain network on influencing credit quality, or more specifically, whether bridging tie (structural network) or strong tie (relational network) of SMEs in the supply chain can improve the availability of equity and debt capital through information sharing. , – A survey was conducted in manufacturing industry in China and 208 valid questionnaires were used to test all the hypotheses. The data were then analyzed by employing partial least squares path modeling. , – The results suggest that both strong tie and bridging tie of SMEs can lead to a positive effect on information sharing in supply chain, which can further enhance the credit quality for SMEs. However, without information sharing, the strong tie has not significant influence on SMEs’ credit quality, while bridging tie can directly impact on credit quality. , – Despite their crucial role in sustaining national economies, SMEs are beset by the critical constraint of risk-free financing. Based on a survey, this research finds that the credit quality of SMEs is affected by two important factors: one concerns information sharing in supply chain and the other relates to the attributes of SMEs’ supply chain network. This study implies that a SME may have a financing advantage for better embedding in the supply chain network, but different effects will be experienced according to constraints associated with information asymmetry in the supply chain.

Supply chain network, information sharing and SME credit quality

The purpose of this paper is to identify the two kinds of supply chain quality management (SCQM) capabilities: intra-SCQM and inter-SCQM, and explore the effect of intra- and inter-food SCQM on food safety and quality, and the effect of food SCQM on domestic and export performance through food certification and corporate reputation.,Secondary data on food selling or processing firms in Western China were collected to test all the hypotheses. The data were then analyzed using the statistical technique of stepwise regression and inference was drawn based on the result.,Through utilizing secondary data sources, it is found that intra-SCQM promotes sales in domestics market with mediating role of corporate reputation, while the realization of overseas performance depend both on intra- and inter-SCQM with mediating role of food certification.,The paper study on food supply chain quality problem, the suggested approaches can be easily realized by agro-food companies to achieve international competitiveness by implementing both intra- and inter-SCQM. Meanwhile to Chinese domestic companies, it is important to strengthen inter-SCQM and food certification in order to achieve competitive advantage.,Review of literature indicated that there is a dearth of open literature that discusses food safety from the perspective of inter- and intra-organizational management. Furthermore, it was also observed that there has been no study that has taken the safety signaling perspective. The current research tires to shed some light on this important, but sparely discussed issue.

Rabia Turson

Papers

Supply chain network, information sharing and SME credit quality

Evaluating the effects of supply chain quality management on food firms’ performance: The mediating role of food certification and reputation