Dynamic Econometric Analysis of Supply Chain Relationship Between China and Five Continents Based on Time Series Regression Model

Dedication. Preface. Times Series Following Generalized Linear Models. Regression Models for Binary Time Series. Regression Models for Categorical Time Series. Regression Models for Count Time Series. Other Models and Alternative Approaches. State Space Models. Prediction and Interpolation. Appendix: Elements of Stationary Processes. References. Index.

In today’s world competition, companies are always in search for new ways to improve the performance of their supply chain, and gather knowledge and skills to reduce time, improve quality and increase productivity. In recent years, Mongolian construction companies started to recognize the importance of supply chain. But there is a limited research and literature on the way how to successfully manage and measure the supply chain performance in Mongolia. The thesis addresses the theory and practice of factors affecting on supply chain performance on the sample of Mongolian construction companies. The study tries to define which factors influence on supply chain performance and which one has the most critical impact in the case construction companies. This study utilized 71 valid responses from 200 surveyed companies in the multiple regression analysis. The findings indicate that supply chain relationship significantly mediates information technology with supply chain performance, whereas environmental uncertainty negatively effects the performance. In addition, the results demonstrate that the supply chain relationship factor is the most critical predictor of supply chain performance. Hence, companies should control the supply chain and gain experience from their mistakes on every stage of supply chain process, and utilize the knowledge in the next phase. The answers of suggested research questions are as follows. The first research question was with which factors can the performance of the supply chain in the construction companies be measured? The results show that information technology, supply chain relationship, environmental uncertainty have positive impact on supply chain performance. The second question was with which factors are most effective in influencing supply chain performance. The results reveals that the most critical factor influencing supply chain performance in Mongolia is supply chain relationship. Since there was no formal information about supply chain performance in Mongolia, this study gives considerable information about supply chain performance in Mongolian companies. Also, it contributed to the limited research on supply chain system in Mongolia and tries to develop a framework for the relationship between affected factors and supply chain performance in case of Mongolian companies. Consequently, it provides insight for experts who would invest in supply chain systems. The result of this study pointed out critical factors for supply chain performance that claim more consideration from managers and engineers to implement supply chain performance successfully. The results of this paper reveal that companies should start the planning stage with a plan detailing the supply chain from it indicators that needed to evaluate success. Without clarifying supply chain desired it companies would not be aware that whether they implementing successfully or not. Without clear indicators and adequate parameters, it is impossible to measure supply chain. Supply chain relationship is proved that it has the strongest influence on supply chain performance. This result asserts the assessment of existing supply chain relationship is required for reaping supply chain performance. Assessments of existing supply chain relationship includes assessing whether the company has supply relation team, building stronger relationships will bring extra security because collaboration with customers and suppliers demonstrates understanding, concern and the desire to work with them over the longer term. Supply chain practitioners continue to press managers to form closer, longer-term relationships between customers and fewer suppliers as the only response to increasing market sophistication and globalization.

PurposeThis study aims to examine the effects of behavioural antecedents of collaboration in supply chain relationships on supply chain integration and performance by developing and empirically validating a model linking these constructs.Design/methodology/approachA conceptual model was developed based on the relational exchange theory, social exchange theory and resource-based view. An international survey with supply chain/logistics managers from manufacturing focal firms based in Europe, USA and Asia was conducted; they provided input on upstream and downstream relationships based on their actual interaction and experience with supply chain partners. The collected data, which reflect supply chain managers’ perceptions on the above described phenomena, were analysed using the partial least squares method.FindingsMutuality, reciprocity, trust and commitment are instrumental for the formation of supply chain relationships characterised by higher information integration. In turn, information integration has much stronger impact on the coordination of operational decisions related to production and demand planning than on decisions related to actual production processes, but, interestingly, the latter affects supply chain performance much more than the former.Research limitations/implicationsThe research could benefit from a longitudinal rather than a cross-sectional approach, incorporating multiple respondents such as representatives of supply chain partners and senior management of the focal firm, to capture potentially varying opinions on the supply chain phenomena under examination.Practical implicationsThe results can assist supply chain decision-makers in understanding the importance of behavioural closeness between supply chain partners for the development of collaborative supply chain relationships that lead to higher integration and superior performance. Insight is provided on linkages between examined dimensions of supply chain integration. A process view of intermediate steps needed to translate collaborative relationships into higher supply chain integration and performance across the supply chain is offered.Originality/valueThe development and testing of an integrated model examining linkages between supply chain relationship antecedents, integration and performance is an original contribution. By proposing and confirming a sequential order of the influence of behavioural antecedents, integration dimensions and their impact on supply chain performance, the paper sets foundations of a roadmap for achieving higher supply chain performance from collaborative supply chain relationships. Finally, the paper contributes to the limited theoretical justification on the development of knowledge for assisting decision-making in SCM/logistics and its integration into models, processes and tasks.

Ensuring security in the current environment, becomes particularly important in both social and economic terms. The changing conditions for business operators are not conducive to ensuring process stability and thus reducing risks in supply chains. It is becoming essential to identify areas, resources and activities that have the potential to ensure process stability and security and reduce uncertainty as well as risk in supply chains. Developing bonds between business partners is particularly important in this regard. Cooperation based on trust ids the basis of such partnerships in supply chains. At the same time, creating such relationships is not only a challenge, but also an additional source of risk. The objective of this paper is to identify the key aspects of relationship formation within companies and their role in ensuring the security of supply chains. Achieving the purpose of the thesis requires the identification of the essence of relationships and relational capital, and the presentation of research findings on key aspects of corporate relationships in supply chains. The research was conducted using a proprietary questionnaire and covered businesses operating in in the metal industry in Poland. The issues examined included such elements as: competences of enterprises in supply chain management in terms of shaping relations: within the enterprise, with customers, suppliers of materials and services, intermediaries (distributors), the number of contractors with whom enterprises cooperate and the level of their relationships, at which they cooperate, involvement of partners/contractors in decision-making, concepts used in relationships with co-operators, type of contracts and partnerships created, measurement/evaluation of cooperation and the scope of control of cooperation with contractors, elements of building trust, factors conducive to cooperation, barriers and reasons for failures in establishing supply chain management relationships. The research thesis is: identifying the relationships of enterprises with contractors has a positive impact on their formation and ensuring the security of supply chains. The research niche presented in the article concerns the use of opinion and judgment research based on the author's survey questionnaire in the environment of enterprises from the metal industry. Obtaining the results allowed to identify the role and scope of business relationships in supply chains and important factors influencing their shaping. The role of managing relationships with business partners as an important element impacting the security of supply chains was also emphasised.

Extensions of quantile regression modeling for time series analysis are extensively employed in medical and health studies. This study introduces a specific class of transformed quantile-dispersion regression models for non-stationary time series. These models possess the flexibility to incorporate the time-varying structure into the model specification, enabling precise predictions for future decisions. Our proposed modeling methodology applies to dynamic processes characterized by high variation and possible periodicity, relying on a non-linear framework. Additionally, unlike the transformed time series model, our approach directly interprets the regression parameters concerning the initial response. For computational purposes, we present an iteratively reweighted least squares algorithm. To assess the performance of our model, we conduct simulation experiments. To illustrate the modeling strategy, we analyze time-series measurements of influenza infection and daily COVID-19 deaths.

The supply chain of agricultural products is the entire production process from cultivation, processing, distribution, and marketing, to the products produced to the hands of consumers. The supply chain consists of various stakeholders who are involved either directly or indirectly. Thus, the supply chain is an integrated marketing unit that includes the integration of stakeholders and products to provide satisfaction to customers. Pinrang Regency is one of the largest rice-producing districts in South Sulawesi. The purpose of this study is to analyze the structure of the inter-island rice supply chain in rice mills in Pinrang Regency, analyze the relationship pattern in the inter-island rice supply chain in Pinrang Regency, analyze the influence of inter-island traders on the rice market in Pinrang Regency, the analysis used is descriptive analysis, panel data regression analysis. The results of this study indicate that the structure of the rice supply chain in the mill starts from farmers who supply grain to the mill, then the mill sells rice to inter-island traders, then the mill sells to wholesalers and retailers then finally the mill sells rice to direct consumers. The rice supply chain in each mill has 3 flows, namely product flow, financial flow and information flow. The pattern of relationships in the inter-island rice supply chain, namely the raw material supply channel (grain), the rice product distribution channel (milling), and the inter-island channel cooperate in completing a purchase transaction and the pattern of relationships in the supply chain uses a general trading partnership pattern. The results of the study using the Common Effect Model (CEM) show that the variable amount of production has a positive and significant effect on the volume of inter-island shipments. The destination price variable has a positive and significant effect on the volume of inter-island rice shipments. Then the variable Shipping cost has a positive and significant effect on the volume of inter-island rice shipments.

The supply chain is the central organizing unit in today's global industries and has gained significance as one of the 21st century manufacturing paradigms for improving organizational competitiveness. In this paper, we propose a dynamic Bayesian network to represent the cause-and-effect relationships in an industrial supply chain. Based on the Quick Scan, a systematic data analysis and synthesis methodology, a dynamic Bayesian network is employed as a more descriptive mechanism to model the causal relationships in the supply chain. Dynamic Bayesian networks can be utilized as a knowledge base of the reasoning systems where the diagnostic tasks are conducted. We finally solve this reasoning problem with stochastic simulation.

This thesis provides practical approaches to supply chain (SC) relationship assessment and monitoring for the fields of collaborative supply chain management (CSCM), supplier relationship management (SRM), customer relationship management (CRM), and partner relationship management (PRM). This work presents relationship analysis results concerning sourcing, demand planning, and logistics processes and relationships based upon a case study conducted at a multinational corporation. These results identified key relationship strengths and weaknesses across three value chains. These results, combined with results from the academic literature, are used to develop an organized list of relationship factors useful for relationship assessment and modeling purposes. The relationship factors are used to create a new Supply Chain Relationship Assessment Model (SCRAM) that incorporates the use of Plan-Do-Check-Act (PDCA) cycles and the use of statistical process control (SPC) to assess, monitor, and manage individual relationship performance. These methods can be incorporated into existing customer, supplier, or SCM software systems. This thesis extends and builds upon the existing academic literature in the fields of marketing, purchasing, and supply chain management, most importantly in developing an approach to quantify the impact of supply chain relationship factors and strategic changes upon overall supply chain performance. More accurate and precise quantification of relationship factors and relationship performance could lead to better selection of SC partners, improve SC relationships, lower SC costs, and increase value for customers.

Purpose: The point of departure in this article is that the principles that underpin entrepreneurial networking also apply to the establishment of supply chain relationships. The theoretical base for the need for entrepreneurial networking can be found in Kirzner's theory of entrepreneurship that argued that entrepreneurs identify and act upon profit opportunities that exist in disequilibrium in order to equilibrate the economy. Problem investigated: This article explores the possibility of implementing entrepreneurial networking in supply chain relationships in the automotive component industry. Methodology: Kirzner's theory is used as a theoretical base to support the case for the development of supply chain relationships. The literature with regard to supply chain management and its relevance to entrepreneurial networking is first dealt with. The case for implementing entrepreneurial networking to strengthen supply chain relationships in the automotive component industry in South Africa is then presented.Findings: The findings of this article indicate that the principles underlying entrepreneurial networking could be applied to supply chain relationships in the automotive component industry in South Africa. The argument is mainly based on the sustainability and profitability potential of entrepreneurial networking and the similarities that exist between entrepreneurial networking and supply chain management relationships. Originality: This research is original as it explores the possibility that the principles that underpin entrepreneurial networking also apply to the establishment of supply chain relationships in the automotive component industry. Furthermore, there is a need for published research in South Africa on supply chain management, particularly relationships within the supply chain.Conclusion: Based on the sustainability and profitability potential of entrepreneurial networking and the similarities that exist between entrepreneurial networking and supply chain relationships, the principles underlying entrepreneurial networking can be applied to supply chain relationships in the automotive component industry in South Africa. The unique challenges facing this industry in the current global market further strengthen the case for the implementation of entrepreneurial networking.

Purpose – The purpose of this research is to investigate the dynamics and dimensions of behaviors of supply chain employees that may impede the success of supply chain relationships. Design/methodology/approach – A grounded theory qualitative method was used to explore the concept of counterproductive work behavior in a supply chain context. Findings – Through analysis and evaluation of the data, five key supply chain counterproductive work behaviors (avoiding, withholding, emoting, confounding, and shifting) emerged. Overall, these behaviors are associated with perceived contract breaches, which undermines trust within supply chain relationships. Research limitations/implications – This work provides a basis for researchers to explore counterproductive work behaviors within supply chain management and managers to consider these behaviors in relational exchange. Future research can build on the insights provided here by applying quantitative methods to exploring the phenomenon and investigating counterproductive behaviors from the actor's perspective. Originality/value – This research provides an overarching framework for relationship management behaviors that may detract from supply chain relationships. Research has previously explored these types of behaviors in a segmented fashion. This work takes a comprehensive look at behaviors and through evaluation of the data, relational and informational contract breaches emerge. The data suggests these contract breaches may undermine the trust within supply chain relationships.

Prioritising Visibility Influencing Factors in Supply Chains for Resilience

Retraction Notice: Viqar Ali Baig and Javaid Akhtar (2011). ‘Supply Chain Management: Value Configuration Analysis Approach: A Case Study’, Vision: The Journal of Business Perspective, 15(3), 251–266. Doi: 10.1177/097226291101500305 has been retracted because this article contains unattributed overlap with material from the following article: Lars Huemer (2006). ‘Supply Management: Value creation, coordination and positioning in supply relationships’, Long Range Planning, 39(2), 133–153. The editor of Vision: The Journal of Business Perspective and the Publisher extend their sincere apology to Dr Lars Huemer. Value creation in the supply chain literature normally builds on the value chain model (VCM). This results in a focus on succedent interdependencies, a focus on coordination by planning and a restricted view of likely positioning options. This article contributes an original approach to the supply chain management (SCM) debate, based on value configuration analysis (VCA). VCA recognizes the value chain logic (VCL), but finds it restraining in particular business systems, and also includes recognition of the value network model (VNM) as representing the layered supply chain relationships (SCRs) classically related with a mediating presence. In general, this article contributes in two ways: by enlightening some of the complexities to be addressed in managing SCRs and by looking at how SCRs function despite this complexity. In particular, it presents an alternative view of how value creation happens between, as well as within, firms in SCRs. It discloses how more complex sets of supply chain interdependencies exist in SCRs than in simple chains, and that these necessitate managing by a variety of coordination machineries to achieve efficient working. Finally, it suggests a novel way to define a firm’s supply chain position beyond that covered by the conventional upstream/downstream terms. These arguments are illustrated with the help of a case study and are related to previous work on supply chains and networks.

Innovation generation has increasingly been recognized as an outcome of interaction between a firm and various outside entities. According to this view, supplier involvement and alliances are routes to innovation generation. Despite this realization, there is a dearth of research, both conceptual and empirical, focusing on innovation generation in buyer-seller relationships in supply chains. In an attempt to fill this void, this article develops a conceptual model of innovation generation in buyer-seller relationships in upstream supply chains. The authors propose that innovation generation in supply chain relationships, both incremental and radical, is a consequence of interactions between buyers and sellers. They also delineate factors internal and external to the relationship that moderate the link between interaction and innovation generation. Finally, the authors discuss managerial implications of their research and offer guidelines for future empirical research.

Supply chain diagnostics with dynamic Bayesian networks

Shifts in the supply of and demand for emergency department (ED) resources make the efficient allocation of ED resources increasingly important. Forecasting is a vital activity that guides decision-making in many areas of economic, industrial, and scientific planning, but has gained little traction in the health care industry. There are few studies that explore the use of forecasting methods to predict patient volumes in the ED. The goals of this study are to explore and evaluate the use of several statistical forecasting methods to predict daily ED patient volumes at three diverse hospital EDs and to compare the accuracy of these methods to the accuracy of a previously proposed forecasting method. Daily patient arrivals at three hospital EDs were collected for the period January 1, 2005, through March 31, 2007. The authors evaluated the use of seasonal autoregressive integrated moving average, time series regression, exponential smoothing, and artificial neural network models to forecast daily patient volumes at each facility. Forecasts were made for horizons ranging from 1 to 30 days in advance. The forecast accuracy achieved by the various forecasting methods was compared to the forecast accuracy achieved when using a benchmark forecasting method already available in the emergency medicine literature. All time series methods considered in this analysis provided improved in-sample model goodness of fit. However, post-sample analysis revealed that time series regression models that augment linear regression models by accounting for serial autocorrelation offered only small improvements in terms of post-sample forecast accuracy, relative to multiple linear regression models, while seasonal autoregressive integrated moving average, exponential smoothing, and artificial neural network forecasting models did not provide consistently accurate forecasts of daily ED volumes. This study confirms the widely held belief that daily demand for ED services is characterized by seasonal and weekly patterns. The authors compared several time series forecasting methods to a benchmark multiple linear regression model. The results suggest that the existing methodology proposed in the literature, multiple linear regression based on calendar variables, is a reasonable approach to forecasting daily patient volumes in the ED. However, the authors conclude that regression-based models that incorporate calendar variables, account for site-specific special-day effects, and allow for residual autocorrelation provide a more appropriate, informative, and consistently accurate approach to forecasting daily ED patient volumes.