Intuitive global sourcing – a study of supplier selection decisions by apparel SMEs

PurposeThe purpose of this paper is to create knowledge on the intuitive global sourcing process applied by small and medium-sized enterprise (SME) managers.Design/methodology/approachThis study reports on qualitative inquiries with experienced sourcing managers from 10 SMEs in the textile industry. The study follows a three-step semi-structured interviewing process, allowing us to gradually unveil the detailed nature of the intuitive supplier selection process.FindingsNine of the 10 SMEs rely on a highly intuitive supplier selections process, where one supplier at a time is gradually taken into the exchange while testing the supplier’s behavior. The process consists of an early heuristics sub-process, which gradually switches over to a more advanced intuiting behavioral pattern-matching process.Practical implicationsMost OM/SCM research has treated global sourcing and supplier selection as a highly rational, analytical and deliberate optimization problem. This study uncovers a completely different, and frequently successful, intuitive process, which could inspire managers in companies of all sizes, faced with high uncertainty about global supplier selection decisions.Originality/valueIntuition has recently been adopted in the global sourcing literature. However, this study is the first to offer detailed insights into a predominantly intuitive global sourcing process, specifically as it is managed by SMEs.

OPTIMISING THE ANALYSIS STAGE IN THE INTERNATIONALISATION OF MANUFACTURING OPERATIONS

The internationalisation of the manufacturing operations process includes decision-making about new facility implementation (NFI) and global supplier network development (GSND), whose first step is to analyse the situation of a company and its environment. The purpose of this paper is to investigate the optimal design of a manufacturing production and distribution network for global small- and medium-sized enterprises (SMEs). This research uses a mixed-integer linear programming (MILP) model to support decision-making in the analysis stage of the internationalisation of manufacturing operations for global SMEs. A real- world case study is presented to illustrate the application of the proposed model. Different scenarios were evaluated not only to identify the strengths and limitations of the mathematical programming model, but to also provide support for the next strategic decisions that the examined company has to make in the near future.

Technological and Economic Decoupling in the Cyber Era

The COVID-19 pandemic has accelerated the shift toward digital services. Meanwhile, the race for technological and economic leadership has heated up, with risks of decoupling that could set back trade and growth and hinder the recovery from the worst global recession since the Great Depression. This paper studies the conditions under which a country may seek to erect barriers—banning imports or exports of cyber technologies—and in effect promote decoupling or deglobalization. A well-known result is that banning imports may be optimal in monopolistic sectors, such as the digital sector. The novel result of this paper is that banning exports can also be optimal, and in some cases superior, as it prevents technological diffusion to a challenger that may eventually become the global supplier, capturing monopoly rents and posing cybersecurity risks. However, export or import bans would come at a deleterious cost to the global economy. The paper concludes that fostering international cooperation, including in the cyber domain, could be key to avoiding technological and economic decoupling and securing better livelihoods.

Engaging a product-focused sales force in solution selling: interplay of individual- and organizational-level conditions

This study explains how manufacturers tackle the critical managerial challenge of transforming a product-focused sales force to undertake solution selling. Through an application of configurational theory, the authors explain how individual and organizational conditions combine to determine salespeople’s engagement in solution selling. Multilevel, multisource data from the sales organization of a global supplier of building solutions represent input from salespeople (N = 184), solution champions (N = 23), and sales managers (N = 26). A fuzzy set qualitative comparative analysis reveals no single, optimal way to overcome transformation challenges. Rather, consistent with prior research, solution selling requires certain types of salespeople, because value-based selling is a necessary condition for successful engagement. Beyond this foundational condition, a heterogeneous sales force can be engaged, as long as the organization provides appropriate support that is tailored to individual salespersons’ needs. The findings affirm that this viable support can come from either sales managers or solution champions.

Novel Multiple Attribute Group Decision-Making Methods Based on Linguistic Intuitionistic Fuzzy Information

As an effective technique to qualitatively depict assessment information, a linguistic intuitionistic fuzzy number (LIFN) is more appropriate to portray vagueness and indeterminacy in actual situations than intuitionistic fuzzy number (IFN). The prominent feature of a Muirhead mean (MM) operator is that it has the powerful ability to capture the correlations between any input-data and MM operator covers other common operators by assigning the different parameter vectors. In the article, we first analyze the limitations of the existing ranking approaches of LIFN and propose a novel ranking approach to surmount these limitations. Secondly, we propound several novel MM operators to fuse linguistic intuitionistic fuzzy (LIF) information, such as the LIF Muirhead mean (LIFMM) operator, the weighted LIF Muirhead mean (WLIFMM) operator and their dual operators, the LIFDMM operator and the WLIFDMM operator. Subsequently, we discuss several desirable properties along with exceptional cases of them. Moreover, two novel multiple attribute group decision-making approaches are developed based upon these operators. Ultimately, the effectuality and practicability of the propounded methods are validated through dealing with a global supplier selection issue, and the comparative analysis and the merits of the presented approaches are demonstrated by comparing them with existing approaches.

Resilient supplier selection to mitigate uncertainty: soft-computing approach

Purpose In recent years, determining the effective and suitable supplier in the supply chain management (SCM) has become a key strategic consideration to the success of any manufacturing organization in terms of business intelligence (BI), as many quantitative and qualitative critical factors are measured from big data. In today’s competitive business scenario, the main purpose of this study is to determine suitable and sustainable suppliers during supplier selection process is to reduce the risk of investment along with maximize overall value to the customer and develop closeness and long-term relationships between customers and suppliers to build a resilient SCM to mitigate uncertainty for automotive organizations. Design/methodology/approach As these types of decisions generally involve more than a few criteria and often necessary to compromise among possibly conflicting factors, the multiple-criteria decision-making becomes a useful approach to solve this kind of problem. Considering both tangible and intangible criteria, the aim of this paper is the presentation of a new integrated fuzzy analytic hierarchy process and fuzzy additive ratio assessment method with fuzzy entropy using linguistic values to solve the supplier selection problem to build the resilient SCM under uncertain data. Fuzzy entropy is used to obtain the entropy weights of the criteria. Findings Organizations gather massive amounts of information known as BD on the basis of historical records of uncertainties from several internal and external sources to manage uncertainty to improve the overall performance of organizations using BI strategy for analyzing and making effective decision to support the managements of automotive manufacturing organizations in an information system. Research limitations/implications Although this study tries to represent a full analysis on suitable and resilient global supplier selection under various types of uncertainty, still there are some improvements that can be made in the future by developing a more refined and more sophisticated approach to further enhance the performance of the proposed scheme to calculate overall rating scores of the alternatives. Originality/value The novelty of this paper is to propose a framework of BI in SCM to determine a suitable and resilient global supplier where all the meaningful information, relevant knowledge and visualization retrieved by analyzing the huge and complex set of data or data streams, i.e. BD based on decision-making, to develop any manufacturing organizational performance worldwide.

King tuna: Indian Ocean trade, offshore fishing, and coral reef resilience in the Maldives archipelago

The traditional offshore pole-and-line tuna fishery of the Maldives has historically promoted low levels of reef fishing in this archipelago. While the tuna fishery is old and extensive—some evidence suggests it has been in place for over a thousand years—the reasons for its development have not been closely examined. Why did an offshore fishery develop in such small and isolated islands with abundant and easily accessible nearshore reefs? Why is tuna considered the “king of fish” in the Maldives, in contrast to many other islands across the globe where reef fish are prized for a wide variety of cultural and social reasons, often deeply rooted in community histories? In this article, we use a historical approach to uncover some of the drivers of this fishery, and the long-term consequences it has had for the resilience of this island chain. We trace the written accounts of travellers, voyagers, and traders, in addition to more recent research to gain an understanding of how early Indian Ocean trade networks may have shaped the development of this fishery over time. We propose that the early growth of the tuna fishery was likely tied to the trade in money cowries (Monetaria moneta), of which the Maldives was a major global supplier. A regional demand and market for dried tuna from the fourteenth century onwards contributed to the income of Maldivians and promoted and supported reef health by encouraging relatively low levels of reef fishing. However, the emergence and substantial growth of the Maldivian tourist industry in the past few decades are resulting in a shift in local consumption preferences and increased exploitation of reef fisheries. Exploring this history is important, not only to help contextualize the modern governance of the offshore tuna fishery, but also for a more nuanced understanding of the social, cultural, and ecological dynamics that have shaped Maldivian coral reefs in the past with implications for those that will do so in the future.