Investigation of capillary tools to reinforce the decision-making capabilities for transforming SCM into smart supply chain management (SSCM)

PurposeThe purpose of this paper is to form an understanding of how new product development (NPD) relates to supply chain management (SCM), why the two fields should be coordinated, and how this may be done.Design/methodology/approachThis research uses a literature review and case study research. The case study considers a Swedish company that operates on a global basis in the furniture industry. Empirical data have been collected mainly from in‐depth interviews with key persons representing senior and middle management in the case company.FindingsThis paper stresses the need to produce innovative, value‐adding products, as well as the necessity to quickly deliver them to the market. Companies that face mature business environments may encounter problems due to a high emphasis on either the value‐creation processes, or on the value delivery processes. Therefore, NPD activities need to be coordinated with SCM activities on a strategic level, lest competitiveness will be lost.Research limitations/implicationsThe research is limited to one case company; replication studies would enhance understanding of the studied phenomenon. There is a wide need for research exploring how various parts of demand and supply chains should be managed in order to fully utilize the advantages of the consumer‐oriented enterprise.Practical implicationsThis paper provides insights for researchers and practitioners on how to coordinate and balance NPD (demand side) with SCM (supply side) activities. It highlights that companies should organize themselves around understanding how consumer value is created and how these processes may be coordinated to provide that value. The two processes must be given equal attention and importance to avoid sub‐optimization.Originality/valueThe need for coordinating NPD and SCM activities has been emphasized in the literature but still remains relatively unexplored. This paper contributes by investigating this issue further.

The purpose of this study is to examine the effects of information utilization and information sharing among supply chain partners on supply chain management (SCM) activities under an uncertain technological environment. This study uses data from 125 manufacturing firms listed on the Korean Stock Exchanges in 2014 in order to testing the impact of information technology and information sharing on SCM. Results revealed that technological uncertainty leads organizations to utilize more sophisticated IT systems and initiate cross-functional teams (CFTs). In addition, IT systems and information sharing among SC partners can contribute to logistics integration and cooperation which are considered as SCM activities. However, CFTscan integrate the flow of goods along the supply chain, but not improve the intention to cooperate with each other. In fact, both IT systems and CFTs undertake the mediating role between technological uncertainty and logistics integration, respectively. Moreover, IT systems also improve the cooperation among SC partners under an uncertain technological environment. Thus, this study suggests that firms should invest their resources in IT systems and encourage CFTs for coping with threats and risks from a rapidly changing technological environment.

This study has been conducted to investigate the relationship between the supply chain management (SCM) activities and operational performance through testing the mediating factor strategic agility in (16) pharmaceutical companies listed on Amman stock exchange in Jordan Which is considered one of the most important industrial sectors, where the nature of the work and the problems faced in the performance of supply chain were identified the reasons for the delay of the logistical orders of raw materials they need from suppliers, and found that there is a missing link between partners and is the proportion of obtaining the necessary information from suppliers to complete operations Streamlined and easy production. In terms of identifying the activities of supply chain management as the most important factors supporting the best practices of SCM in pharmaceutical companies (i.e. Alliances with suppliers, Customer Relation Management, Logistic, flow Information and knowledge sharing). The study population consisted of all the executives and directors of departments, sections and employee specialized in SCM in pharmaceutical companies, and a simple random sample was chosen from pharmaceutical companies to conduct a field survey using a tool, a questionnaire, of which 150 were distributed and 139 were retrieved. In addition, a number of statistical techniques have been used for data analysis; such as statistical analysis package for Social Sciences (SPSS) and AMOS, which depends on Structure Equation Modeling approach because of the presence one variable, as well as for the reason of examining the importance of the track. Based on the results of the statistical analysis, it was concluded that there is an impact of the independent variable managing the supply chain on operational performance, but in terms of the intermediate variable, the results showed that the relationship is partial in terms of the strategic agility variable through Path Analysis.

Demand management is complex and crucial coordinating activity in supply chain management. Its roots are at retail echelon of supply chain where it is most efficiently conducted through category management process. This chapter aims to highlight the importance of category management for efficient demand management activities in the retail supply chain management through a theoretical analysis of the category management process. The need for cooperation between retailers with other members of the supply chain in category management is also emphasized, especially in form of category captainship collaboration. Category management run by retailers is the beginning and precondition for efficient and effective demand management throughout the whole supply chain. Potential implementation problems in certain areas of demand management in retailing are pointed out, and finally solutions for overcoming these issues are offered.

Smart supply chain management aims to transact more efficiently, quickly, and flexibly by integrating artificial intelligence, big data analytics, machine learning, and other digital technologies into traditional supply chain management processes. With globalization and digitalization reaching significant dimensions, integrating digital technologies in business models is extremely important. In this way, blockchain technology offers a reliable and tamper-proof structure. With the rapid development of technology, the potential of blockchain in smart supply chain management is increasing. Businesses have to integrate blockchain technology into smart supply chain management. For this reason, it is necessary to know the emerging trends for blockchain technology in smart supply chain management. Therefore, the present study focuses on the blockchain technology on smart supply chain management. Accordingly, the aim is to identify emerging trends for blockchain technology on smart supply chain management by using Vosviewer from systematic literature review perspective.

Supply chain management (SCM) in the apparel industry was empirically examined through a quantitative research design. The objectives of the study were to identify the level of SCM activities and to examine the relationship of selected company characteristics for a set of US apparel manufacturers. Through the literature review, six dimensions of SCM (i.e. partnership, information technology, operational flexibility, performance measurement, management commitment, demand characterization) were identified. US apparel manufacturer groups, based on their SCM activity levels, showed statistically significant differences in company characteristics including product fashion level, fabric supplier delivery performance, relationship with fabric suppliers and retail customers and relative size of retail customers. For example, a high level of SCM activity implementation is closely related with the characteristics of more basic goods production, higher delivery performance of fabric supplier, and relatively big retailers. These manufacturers also had more partnership‐like relationship with their supply chain members.

In this study, the researchers have attempted to determine the common Supply Chain Management (SCM) activities that were used as a mediator variable and influenced the effect of the product development stages on the implementation of operation management decisions in the companies belong to the Al-Manaseer Group in Jordan. For this purpose, they used a quantitative method, wherein they distributed questionnaires to the employees and management of the Al-Manaseer Company groups (such as the Director, Department Director, Head of the Section, Workers' Monitor). This helped them understand the relationship between the product development stage and the operational management decisions. They noted that the SCM activities were a significant variable that mediated the effect of the product development stage on the operational management decisions. Based on the findings of the study, the researchers recommended that The Group needs to show a higher interest in the site costs as the selection indicator and for determining the preliminary estimates while considering the information sharing.

The technology in supply chain today has evolved significantly; to be more efficient and offers value added to the manufacturing firms. The concept of Industry 4.0 in supply chain management denotes the transformation of manufacturing processes through digitalization and automation. It has the potential to provide high-impact transition to supply chain management as a whole. Thus, to transform from the conventional supply chain to the smart supply chain management, it requires a thorough assessment in terms of the drivers that are able to motivate the manufacturing firms and also the challenges that might encounter if the manufacturing firms consider to adopt the concept of Industry 4.0 in the supply chain management. The purpose of this paper is to analyze the drivers and challenges of adoption of the concept of Industry 4.0 in order to create smart supply chain management using a systematic review.KeywordIndustry 4.0Supply chain managementSmart supply chain managementInternet of thingsIoT

From the origin of man's study of space comes guidance on today's security matters - particularly as they impact and place burdens creating challenges for effective logistics and supply chain management activities. There is evidence that observations and experiences from space throughout the millenniums have inspired ways to enhance security and to minimize vulnerabilities while facilitating the teaching of logistics and supply chain management. Security issues that are being dealt with today strategists and planners responsible for the transport and safe-keeping of goods and the well-being of logistics services providers include that of the threat and response; global positioning systemization for remote sensing capabilities within passive and active RFID systems; software algorithms capabilities built into equipment to allow intelligent or smart decisions to be made in remote areas of operation; observation of earth for the forecasting and monitoring of natural disasters and of organize crime, as well as the armed threat of forces from an adversary; new communication techniques, small satellites for facilitating surveillance and communications; design and construction of logistics support structures; solar panel energy power generation; international cooperation in space activities through global sourcing processes and other such space-influenced initiatives. Today as Turkey embarks on the procurement and contracting with satellite manufacturers for the oversight of the building and launching of its first military/defense satellite priority for communications and surveillance operations, there is the recognition that an opportunity may exist for university students to become familiar with important methodological processes dealing with the acquisition by Turkey of certain aeronautical and space technologies - the bases of which can include a look at such applications and their connection to security needs within logistics and supply chain management activities. With this relatively late focus on Turkey's expansion into space, there may exist an opportunity to capture further the students' imagination into another dimension - that of the exploration of space as a source of tools for dealing with security issues. Recognition of this opportunity may be the initial step toward the inclusion of these issues into the development of the university course offering. Such a course would serve as a tool for teaching/training students to become familiar with the methodology for the appreciation of the global impact of space technologies as part of the logistics and supply chain program of study. It may further allow the student to gain insight about such programs and also may help to create more robust discussion and innovative thinking about development of the logistics and supply chain infrastructure. Such educated and trained students, during the course of their chosen career fields, may contribute by their seeking to be included in the planning sessions for collaboration on the security aspects of related projects - the objective being to find new ways to strategize Turkey's participation in the various logistics and supply chain management programs and thereby maximize returns to the country.

Research interests in machine learning (ML) and supply chain management (SCM) have yielded an enormous amount of publications during the last two decades. However, in the literature, there was no systematic examination on the research development in the discipline of ML application, in particular in SCM. Therefore, this study was carried out to present the latest research trends in the discipline by analyzing the publications between 1998/01/01 and 2018/12/31 in five major databases. The quantitative analysis of 123 shortlisted articles showed that ML applications in SCM were still in a developmental stage since there were not enough high-yielding authors to form a strong group force in the research of ML applications in SCM and their publications were still at a low level; even though 10 ML algorithms were found to be frequently used in SCM, the use of these algorithms were unevenly distributed across the SCM activities most frequently reported in the articles of the literature. The aim of this study is to provide a comprehensive view of ML applications in SCM, working as a reference for future research directions for SCM researchers and application insight for SCM practitioners.

Radio-frequency identification (RFID) has been a very crucial element when it comes to the Internet of Things (IoT). Its low cost, small form factor, and multiple items tracking make it suitable to use in Smart Supply Chain Management (SSCM). There are many limitations of traditional Supply Chain Management (SCM) such as decentralized control, slow process, a lot of manual bookkeeping, unpredictable supplies which can lead to uncertain prices and deliveries. This paper discusses how SSCM can help overcome these drawbacks, by investigating four different scenarios of SSCM where RFID plays a major role. The frameworks discussed here try to solve some parts of the SSCM and give a brief idea about how they can be incorporated into the whole process. In addition to examining different approaches, a combined framework is proposed at the end. This proposal reflects the best characteristics that can demonstrate the versatility of RFID for tracking products, inventory management, and security aspects in SSCM.

Industry 4.0 (I4.0) is an innovative way of improving organizations' production methods by using new technologies that revolutionize the Supply Chain (SC). Traditionally, SC managers focused on simple tasks such as delivering products to customers and assuring that a company maintains a sufficient supply of raw materials to sustain ongoing operations. However, with the fast progress in logistics, SC Management (SCM) has become a complicated process involving forecasting demands, establishing lucrative partnerships, and optimizing business performance. To overcome this challenge, Smart Supply Chain Management (SSCM) uses several technologies such as Big Data (BD), the Internet of things (IoT), Blockchain, Artificial Intelligence (AI), and Advanced Robotics (AR) to analyze data, and identifies trends and opportunities in the market that enhance the effectiveness of logistics, whether inside or outside of the company. This paper examines the available literature on SSCM. It aims to assess the impact of new technologies on SSCM.

Supply chain management (SCM) is the integration and strategic alliance involving all the value-creating elements in the supply, manufacturing, and distribution processes from raw material extraction, the transformation process, and end user consumption. This paper explores the SCM activities carried out by electronic manufacturing organizations in Malaysia and determines the correlation between SCM practices and firm performance. A self-administrated questionnaire based survey technique was employed to ascertain the status of SCM adoption and the practices in SCM that are significant for Malaysian electronics manufacturers. The findings suggest that the adoption of SCM activities is reasonably moderate.

This paper examines the potentials of augmented reality (AR) technology in supply chain management (SCM) and logistics. Specifically, we provide an overview of the technology’s various value propositions and its ability to support companies’ business processes. Although the emergence of Industry 4.0 has renewed the interest in AR, and how it can address several issues challenging existing business models, rigorous studies investigating the potentials of AR for SCM and logistics activities are scant. To bridge this knowledge gap, we conducted a systematic literature review to compile existing literature, identify current research gaps, and systematize AR research in SCM and logistics activities. In total, forty-three (43) papers were thoroughly analyzed. The findings of this study reveal that AR can add value in five main areas, namely warehousing, manufacturing, sales and outdoor logistics, planning and design and human resource management. Moreover, we discuss organizations’ challenges when deploying AR in SCM and logistics and propose exploratory research opportunities for further investigation. In this paper, we highlight numerous practical implications of AR in SCM and recommend that organizations consider AR as a potential solution for enhancing business processes, improving operational efficiencies, and increasing overall competitiveness. This study represents one of the first attempts to synthesize AR’s literature from an SCM and logistics perspective.

In recent time, the application of data analytics (DA) has grown significantly in virtually every field, Supply Chain Management (SCM) being one of them. DA processes like CRISP-DM serve as an orientation framework for managing DA projects in general but fail to deliver domain-specific details at the operative project level especially in SCM. Setting DA objectives, deriving associated SCM activities, identifying applicable measurement indicators for analyzing these activities, as well as defining DA questions for the specific DA objectives are challenging and under-researched tasks. This paper presents a literature review- and expert questionnaire-based approach for conducting the business understanding stage of CRISP-DM in SCM DA projects. The developed approach provides a procedure for selecting and defining the right DA questions based on specific DA objectives and SCM activities. To demonstrate applicability of the research, the DA approach is applied to an ongoing DA project in retail SCM. The result show that the time required for completing the business understanding stage of the DA project could significantly be reduced. Furthermore, the DA questions developed in this study provided a clear guideline for the project and facilitated cooperation between data analysts, research and SCM domain experts.