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Only a limited amount of research has been reported on factors influencing international location decisions for contemporary manufacturing operations. In this paper a comprehensive set of factors that may influence international location decisions is identified from an analysis of the existing literature. Results are presented from a Delphi study that used a worldwide panel of experts to investigate factors affecting international location decisions. Findings are reported on the motivations of firms in seeking to manufacture across national borders and the key steps that should be followed in making international location decisions. The top five major factors identified that may strongly influence international location decisions generally were: costs, infrastructure, labour characteristics, government and political factors and economic factors. Ten key sub‐factors identified were: quality of labour force, existence of modes of transportation, quality and reliability of modes of transportation, availability of labour force, quality and reliability of utilities, wage rates, motivation of workers, telecommunication systems, record of government stability and industrial relations laws. Additional sub‐factors of increasing importance include: protection of patents, availability of management resources and specific skills and system and integration costs. The factors identified have implications for management practice, for policy‐making by governments and other agencies and for academic research in international operations.

This paper aims to investigate the application of unsupervised machine learning in the international location decision (ILD). This paper addresses the need for a fast, quantitative and dynamic location decision framework.

Unsupervised machine learning technique, i.e. k-means clustering, is used to carry out the analysis. In total, 24 different indicators of 94 countries, categorized into five groups, have been used in the analysis. After the clustering, the clusters have been compared and scored to select the feasible countries.

A new framework is developed based on k-means clustering that can be used in ILD. This method provides a quantitative output without personal subjectivity. The indicators can be easily added or extracted based on the preferences of the decision-makers. Hence, it was found out that the unsupervised machine learning, i.e. k-means clustering, is a fast and flexible decision support framework that can be used in ILD.

Limitations include the generality of selected indicators and clustering algorithm used. The use of other methods and parameters may lead to alternate results.

The framework developed through the research intends to assist the decision-makers in deciding on the facility locations. The framework can be used in international and national domains. It provides a quantitative, fast and flexible way to shortlist the potential locations. Other methods can also be used to further decide on the specific location.

This paper aims to provide organizations with a new tool to make decisions related to a facility (building) selection process. Traditionally, value engineering (VE) applies the Value = Function/Cost formula to evaluate the worth of a product. In this paper, the VE-based facility-selection approach is proposed, where the cost of a facility is expressed in net present value (NPV) as it contains the net expense of purchasing or leasing a building as well as the time value of money. Also, a method of quantifying functions and involved risks of different facility choices is proposed.

The framework of the VE-based facility-selection process is broken down into three steps: preparation, calculation/analysis and assessment. In the latter part of this paper, the authors share a sample analysis by illustrating the analysis and decision-making process when three hypothetical facility-selection options are available.

The sample analysis indicates that companies can get the lowest cost and risk while improving their functions to achieve the highest value by using the modified VE formula to drive an optimal option for company’s business expansion and facility-selection process.

This paper provides organizations with a strategic system and process to select proper facilities or buildings for business expansion. The VE approach suggested in this study can allow facility/real estate portfolio decision-makers to analyze financial and functional aspects of the facility at the same time and obtain the value coefficient when they choose a new facility from different options. Finally, they can select the best option, which has the highest value coefficient, given financial and functional considerations.

The purpose of this paper is to identify and prioritise the success factors and challenges related to competitive manufacturing (CM) capabilities in a high-cost environment, and identify their potential to support future reshoring in textile and clothing (T&C) supply chains, with judgements from the practitioners’ perspective.

A Delphi study method is adopted with industry practitioners from the region of Western Sweden. Following a literature review on reshoring to identify relevant factors related to CM capabilities, a multiple round Delphi is designed to rank the success factors and challenges, and to further evaluate the likelihood of the success factors to lead to future reshoring. Additional semi-structured interviews are conducted to provide deeper explanation.

Empirical insights are both conforming to, and deviant from, evidences from extant literature. Moderate agreement is seen among the practitioners on the success factors; time- and product/process-related ones being ranked the highest. Low consensus is reached for the challenges, however, those related to high costs and lack of local resources were key concerns. Some anomalies from previous conception emerge among the challenges regarding increased costs of production, inventory and product variety trade-offs, and low skillset presence.

The paper contributes to reshoring research by identifying and prioritising value-driven success factors and cost-related challenges to CM in high-cost environments, for labour-intensive T&C industries. In connection, some interesting paradoxes originate when dealing with multiple success factors.

Valuable insights are generated for informed decision making related to CM and future choice of its location.

Along with the decisive knowledge of the reshoring success factors and challenges, the study offers an interesting T&C practitioners’ perspective.

The purpose of this paper is to analyse which are the motivations for implementing two of the most important models for Quality Management practice popularized in recent years – ISO 9000 and EFQM models.

This paper provides a qualitative survey carried out using the Delphi methodology, triangulated with the results of other surveys carried out previously, as well as with the information gathered by means of several in‐depth interviews carried out with the experts that participated in the Delphi‐panel.

The paper finds strong consensus among experts of different backgrounds that external factors cause companies to implement the ISO 9000 standard. On the other hand, reasons for implementing TQM systems seem to be more varied.

The research in this paper is limited to Spain; studies in other countries should be conducted to compare the results obtained.

In this paper there is a greater understanding of the motivation to implement ISO 9000 and EFQM based on the opinion of managers, consultants, academic specialists and members of institutions.

The paper finds a new methodology for examining the motivation to implement ISO 9000 and EFQM.

The purpose of this paper is to identify and prioritize the corporate sustainability practices to improve the corporate sustainability performance in the manufacturing sector. Further, these practices are being prioritized to find out the essential practices to ensure logical allocation of limited resources.

It examines the corporate sustainability practices which have been shortlisted from both the literature review and experts judgment. Then, analytic hierarchy process has been used to assess the identified 12 practices of corporate sustainability and to find their priorities for improvement of the corporate sustainability performance.

Based on the hierarchical model developed in this study, the analysis reveals market value, environment management and strategy, research and development, pollution prevention, corporate governance and investor responsibility, which have been found to be the most important practices in improving the corporate sustainability performance.

The findings of the study would be useful to the practitioners in the proper allocation of scarce resources to optimize the corporate sustainability performance of firms, especially the manufacturing entities.

It is a fact that multi-faceted nature of corporate sustainability includes both subjective and objective dimensions. Therefore, prioritization of corporate sustainability at the factor level is one of the important contributions to the literature that has been addressed in the present study. The results of this paper may be generalized to the other sectors.

A number of literature contributions have underlined the importance of developing value-added logistics activities or VALS in order to help improve customers’ satisfaction. However, there is usually very little attention given regarding where to perform these VALS. This study aims to: (1) identify a comprehensive set of factors which may influence the location of VALS, (2) to analyze to what extent those factors influence location decisions, and (3) to distinguish the determinants behind the location choices for distribution centers and for the kind of VALS that will be developed in these distribution centers.

In this paper, we will present a conceptual framework on the locations of VALS in view of the identifying determinants for assigning VALS to logistical centers. We argue that the optimal location of VALS is determined by complex interactions between the determinants at the level of the choice of a distribution system, distribution center location factors, and different logistical characteristics regarding products.

The dynamic nature of uncertainty sources in regional operations represents supply chain management (SCM) imperatives to review uncertainty management frameworks on an ongoing basis with a view to identifying and prioritising critical indices of uncertainty for effective SCM. The purpose of this study is to identify the critical indices of uncertainty for regional supply chains and analyse how SCM practitioners perceive uncertainty.

This paper presents a Delphi-based study with a panel of 70 SCM experts from the Sultanate of Oman in the Gulf Cooperation Council (GCC) region. It applies three rounds of a Delphi exercise to identify, select and prioritise the critical indices of supply chain uncertainty perceived by panel experts. The thematic analysis also provides theorisations on the process for uncertainty perception and factors shaping perception.

A total of 39 uncertainty indices were identified from demand, supply, manufacturing, control, technology, competitive, project, transport and geological sources. The Delphi selection round captured the top 12 indices of experts. The research found an accumulative–aggregative duality that explains uncertainty perception and a cost–conformance–connection triadic set of factors underlying the perceived critical indices. Project uncertainty produced the top-ranked index in the final Delphi round.

This paper makes three main contributions. First, it offers a bottom-up based insight into supply chain uncertainty using the Delphi-based study and from a GCC perspective. Second, the research is unique in its focus on Oman and, third, it is of value for the international operations of GCC companies and for international firms with intentions of expanding, moving or outsourcing their operations to a GCC country such as Oman.

Organic rice forms the largest portion of the Thai organic food market. Because of its increasing popularity, marketers need to better understand consumer behaviour to address emerging concerns regarding product safety and quality and to tailor better marketing strategies relevant to the development of organic rice. As such, this study aims to examine consumers' purchase intention towards organic rice, using traceability information, and to investigate the direct and moderating roles of product traceability knowledge, using the theory of planned behaviour.

Responses were collected from 243 organic rice consumers in a farmers' market in Chachoengsao Province, Thailand, following a convenience sampling approach. The gathered data were analysed using structural equation modelling to evaluate the strength of the relationship between the constructs.

The findings reveal that subjective norms, health consciousness and product traceability knowledge have a significant positive influence on consumers’ intention to purchase organic rice. This study also establishes the moderating role of product traceability knowledge in perceived behavioural control and purchase intention, indicating that elaborated product information through traceability is essential for consumers who feel capable of buying the product. However, the direct effects of attitude and perceived behavioural control are insignificant, indicating the presence of external barriers to the purchase of organic rice, and that people may have a negative attitude towards the product. In addition, the cost perception result reveals that consumers consider price as an indicator of organic product quality, thereby increasing their desirability.

The findings of this study will help community enterprises in Thailand develop a more effective marketing strategy based on the identified motivators of organic rice purchase intention.

This study develops a model that integrates important factors related to organic food consumption to generate a more comprehensive analysis of this mainstream research. To the best of the authors’ knowledge, this is also the first study to investigate the moderating role of product traceability knowledge to obtain a new and more focused understanding of how this factor influences purchase intention when applied explicitly to organic food. Finally, the findings provide theoretical contributions and implications for both the community enterprise and policymakers on developing strategies for organic rice marketing among community enterprises in Thailand.

This paper aims to report on the results of a study carried out to establish the contribution of business choice and location decision to the success of small and medium enterprises in an emerging economy like Uganda.

This study is cross-sectional and correlational. Data were collected through a questionnaire survey of 181 small and medium restaurants. The data were analyzed through correlation coefficients and hierarchical regression using statistical package for social sciences.

The findings reveal that both business choice and location decisions positively and significantly contribute to the success of small and medium enterprises. However, it was noted that more attention should be paid to location decision than business choice as determinants of SME success.

To the authors' knowledge, this is the first study to investigate the contribution of business choice and location decision to the success of SMEs using evidence from a developing African country like Uganda. Finally, this research offers practical contributions to managers and owners of SMEs who have to make strategic decisions for firm profitability, survival and growth in the competitive business arena.