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This study aims to identify key supply chain challenges and opportunities of the case of Hong Kong toy manufacturing company during the COVID-19 outbreak and develop a comprehensive structural relationship to rank them.

In this study, a toy model company in Hong Kong is considered to discuss about what challenges and opportunities have the biggest impacts on non-necessary goods companies and how to deal with different impacts on entire supply chain flow disruption during COVID-19. A semi-structured interview with five decision-makers from the company was made to give key challenges and opportunities scores. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) technique is used to establish the model and rank them afterward to overcome the challenges.

From the data analysis and results, “salary of employee” and “inconvenient transportation” have emerged as top and bottom key challenges respectively. The sequence of organized challenges in the list needs to mitigate one by one in this order to improve the supply chain performance. The “client's orders’ frequency, customer management” and “supplier/partner relationship management” are identified as the top and bottom respectively to develop the opportunities.

These key challenges and opportunities are identified as contributing attributes and provide the way to measure to improve production, profits and sustainable growth of the toy manufacturing company during a pandemic. Moreover, it helps to improve the distribution level and good planning with appropriate decision making to manage the supply chain performance considering humanitarian aspects during a pandemic outbreak.

The novelty of this study is to identify the key supply chain challenges and opportunities measured by the TOPSIS method to rank them and consider the case of a Hong Kong toy manufacturing company as a case-based approach to measuring its performance during the COVID-19 outbreak.

Examines the research of integrated product design. Several design strategies and methodologies have been proposed, yet none of them is particularly suitable for small‐to medium‐sized enterprises. Develops strategies of integrated product design for small‐ to medium‐sized companies through the studies of the Hong Kong toy manufacturing industry. These include strategies for the product design, the assembly system design and computer‐aided tools. Uses a case study to illustrate some of the concepts of the integrated product design. Finally, discusses the application and limitations of the proposed integrated product design methodology.

An organization’s supply chain is the upstream fraction of the value chain activities, aiming to ensure that the right materials, services, and technologies are purchased from the right sources, at the right time, and in the right quality. It is essential that a company is able to utilize its supply chain with the support of a good monitoring scheme. This paper considers a framework of supply chain management embracing the principles of fuzzy logic for analyzing and monitoring performance of suppliers based on the criteria of product quality and delivery time. The proposed system recommends the quantity that should be placed in the next purchase order by indicating the possible issues to be considered prior to final confirmation with the relevant suppliers.

This article examines the careers and changing roles of British production and operations managers through three surveys covering the last quarter of the twentieth century. Careers are examined in terms of both their organisational context and the subjective experiences of those who have chosen this field, during a period of great turbulence for manufacturing due to growing global competition. The persistent features of such roles and responsibilities are contrasted with the changes in focus and demands. The managers' sources of satisfaction and frustration are outlined as are their perceptions of their situation in relation to managers in other areas. The article concludes by considering what has changed and what needs to change, in order for manufacturing to gain maximum benefit from the contribution of these managers.

The purpose of this study is to survey knowledge management (KM) practices and to examine the applications and technologies adopted when developing the knowledge management system (KMS) in build‐to‐order supply chains (BOSC).

This paper uses a literature review of research articles from 1996 to 2007 with keyword indexes to survey the KM practice, KMS technology and its application in BOSC. Such keyword indexes include: BOSC, SCM, KM, KMS, expert system, knowledge‐based system and information system on the Elsevier online database, ScienceDirect, EBSCO, Proquest, Emerald, DOAJ, and Wiley Inter Science. A total of 1,500 articles were found but only 149 articles related to the keywords of KMS application and KM practices within SCM and BOSC.

The important findings indicate that the KMS application is solely focused on single knowledge problem for enabling individual SC members to attain operational excellence. There is a need for further research into the development of KMS with features of knowledge coordination that cross organizational borders in attaining the BOSC integration.

Perhaps, the limitation of this study was the narrowness of the scope of the paper based on the keywords used for searching.

Validation of the multi‐disciplines of KM practices and KMS applications provides enterprises with useful guidelines for implementing KM‐ and KMS‐related projects within their current BOSC practices.

This paper provides useful knowledge by highlighting the characteristics of KMS technology within BOSC and empirical insights into the relationship between KM and BOSC practices.

To propose an infrastructure of a knowledge‐based system to capture and maintain the procurement information and purchasers' knowledge, regarding how to choose partners in the supply chain network, with the adopting of the neural networks that mimic the operation of human brain to generate solutions systematically.

The proposed system encompasses hybrid artificial intelligence (AI) technologies, Online analytical processing (OLAP) applications and neural networks.

Be able to capture the procurement data and vendors' information that are generated in the workflows to ensure tthat he knowledge and structured information are captured without additional time and effort. Recognizes the void of research in the infrastructure of the hybrid AI technologies for knowledge discovery.

Neural network does not have the sensibility characteristic of the purchasing staff, it is not able to identify the environment changes, which need to re‐adjust the output to fit the environment.

The proposed system obtains useful information related to the trend of sales demand in terms of customer preference and expected requirement using the OLAP module and then based on this information, the neural network provides recommendation related to the supported suppliers that are capable of fulfilling the requirements.

This paper proposes a knowledge‐based system that offers expandability and flexibility to allow users to add more related factors for analysis to enhance the quality of decision making.

Even the greatest developed countries have capitulated to the destructions imposed on the global supply systems, as the COVID-19 pandemic has revealed. The purpose of this study is to explore human resource sourcing strategies for managing supply chain performance during the COVID-19 outbreak. There are six human resource sourcing strategies such as outsourcing, near sourcing, integration, the requirement of suppliers, joint ventures and virtual enterprise that are considered to measure supply chain performance.

Based on collecting data from the potential respondents of Indian manufacturing companies, the elevation of human resource sourcing strategies to supply chain performance is measured considering the multiple regression analysis techniques.

The results of the study revealed that four of the six hypotheses have a significant and positive relationship with supply chain performance during the COVID-19 outbreak while two hypotheses are partially supported that lent good support to this study.

In this critical situation, this study will enable managers and practitioners to support the business in giving customers the best services on time.

The novelty of this study is to identify the key human resource sourcing strategies by using multiple regression analysis methods, considering the case of Indian manufacturing companies to measure their supply chain performance during the COVID-19 outbreak era.

The purpose of this study is to examine the development of a protean career orientation. In doing so, the paper also aims to assess how work experience, parents and peer networks co‐influence the development of a protean career orientation.

The paper uses semi‐structured interviews with young adults and explores their past, present and future work and career experiences. They were also asked them to explain what career success meant to them. Interview transcripts were reviewed and coded based on two main categories representing protean orientation: self‐directed career management and the expression of personal values as a mechanism for career decisions. The paper also process mapped how a protean career orientation developed in the interviewees. Those who reported a protean career orientation were interviewed two‐and‐a‐half years later so as to further explore their career experiences and the extent to which self‐directedness and value congruence influenced career decisions.

Results suggest that some reported a protean career orientation and of those that did they reported experiencing an image violation based on their personal values. Two types of personal values appeared important to the protean group, they were, making a contribution to society and maintaining work‐life balance. Those that were categorised as having a protean orientation also engaged in critical reassessment by interrogating the basis of their career values and strategies and this distinguished them from the rest of the interviewees who exhibited a more traditional career orientation. These findings are consistent with image theory's concept of a progress decision. This concept encapsulates the idea that individuals decide whether a career plan is moving them towards achievement of a career goal and if it is not, new or modified plans need to be taken up.

The exploratory findings have important implications for understanding the career strategies of protean careerists. Specifically, they elucidate how violations of values, goals and plans lead to career reappraisals. This paper provides important insights into reframing career choice and change in terms of image violations.

The paper provides a process map of the mechanisms that contribute to the development of a protean career orientation. Specifically, it focuses on image violations that appear to distinguish protean careerists from the remainder of the interviewees. Thus, the paper links protean careers with image theory as a means of understanding the underlying processes involved in early career decision making.

Despite the current progress in realizing how Big Data Analytics can considerably enhance the Sustainable Manufacturing Supply Chain (SMSC), there is a major gap in the storyline relating factors of Big Data operations in managing information and trust among several operations of SMSC. This study attempts to fill this gap by studying the key enablers of using Big Data in SMSC operations obtained from the internet of Things (IoT) devices, group behavior parameters, social networks and ecosystem framework.

Adaptive Prospects (Improving SC performance, combating counterfeits, Productivity, Transparency, Security and Safety, Asset Management and Communication) are the constructs that this research first conceptualizes, defines and then evaluates in studying Big Data Analytics based operations in SMSC considering best worst method (BWM) technique.

To begin, two situations are explored one with Big Data Analytics and the other without are addressed using empirical studies. Second, Big Data deployment in addressing MSC barriers and synergistic role in achieving the goals of SMSC is analyzed. The study identifies lesser encounters of barriers and higher benefits of big data analytics in the SMSC scenario.

The research outcome revealed that to handle operations efficiently a 360-degree view of suppliers, distributors and logistics providers' information and trust is essential.

In the Post-COVID scenario, the supply chain practitioners may use the supply chain partner's data to develop resiliency and achieve sustainability.

The unique value that this study adds to the research is, it links the data, trust and sustainability aspects of the Manufacturing Supply Chain (MSC).