Benchmarking supplier external risk factors in electronic equipment industry supply chains

Modeling of factors affecting supplier selection on start-ups during frequent pandemic episodes like COVID-19

Purpose

In developing countries such as India, start-ups play an essential role in “industrial output,” “Gross Domestic Product ” and “employment creation.” Evidence suggests that pandemics have risen over the last century due to rising global travel and assimilation, urbanization, alterations in land use, and significantly larger exploitation of the natural environment. These trends are likely to continue and intensify. These pandemic episodes affect businesses, especially start-ups. Supplier selection is among the vital critical elements that start-ups must include in start-ups' strategy procedures during the pandemic episodes. This study's focus is to “identify,” “analyze,” and “categorize” the factors affecting supplier selection in start-ups during frequent pandemic episodes like coronavirus disease 2019 (COVID-19).

Design/methodology/approach

Through “literature review” and “experts' opinion” from various start-ups in India, ten affecting factors were identified. Total Interpretative Structural Modeling (TISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) were employed to analyze the interrelationship among the factors affecting the supplier selection on start-ups during frequent pandemic episodes, and these factors were ranked as “autonomous,” “independent,” “linkage,” and “dependent” factors.

Findings

The findings show that “performance history,” “service levels,” “technical capability,” and “financial stability” are the most critical factors affecting the supplier selection on start-ups during frequent pandemic episodes. The next importance should be safety and environmental concern” and “quality.”

Research limitations/implications

The factors affecting supplier selection on start-ups during frequent pandemic episodes are the current focus of this study. This study is mainly performed on Indian start-ups and can be extended to other countries.

Practical implications

The start-ups can rely on this study to clearly understand the factors affecting the supplier selection on start-ups during frequent pandemic episodes.

Originality/value

There is no research regarding factors affecting supplier selection on start-ups during the COVID-19 emergencies. This research gap is filled by analyzing aspects linked to supplier selection in start-ups. This gap inspired the present study, which employs the “Total Interpretive Structural Modeling (TISM)” technique to uncover supplier selection determinants and investigate hierarchical interconnections among factors influencing/affecting supplier selection in start-ups during frequent pandemic episodes.

Procurement process risk and performance: empirical evidence from manufacturing firms

Purpose

This paper employs the positivism paradigm, quantitative approach and explanatory research design. It analyses primary data obtained from manufacturing firms via structured questionnaires and uses the partial least square-structural equation modelling technique to establish the effect of individual procurement process risk on procurement performance.

Design/methodology/approach

Procurement risks are inevitable in manufacturing procurement process; a situation that could undermine the performance of manufacturing firms if not properly managed. Yet, with procurement accounting of about 14–19% of developing countries gross domestic product, the effects of procurement process risk on performance remain scarce in manufacturing firms in developing countries. Therefore, the paper aims to investigate the effect of procurement process risk on procurement performance of manufacturing firms.

Findings

In this paper, five out of the six procurement process risks studied were found to be undermining procurement performance of manufacturing firms significantly. However, the risk threshold effect on the performance differs.

Research limitations/implications

Although this research is geographically/sector bias, several insightful managerial implications can be drawn to manage procurement process risk in manufacturing settings irrespective of the area of operation. The results of this research imply that manufacturing firms' procurement process is risk prone and the effect of risk surrounding each procurement process on procurement performance differs. Hence, the need to identify and analyse the risks surrounding each procurement process before making managerial decision to spend firms limited resources in response to the individual risk to improve procurement performance in the manufacturing sector.

Originality/value

This paper is the first to provide existing and future procuring practitioners/firms with in-depth empirical evidence of the effect of the procurement process risks on procurement performance in manufacturing firms operating in developing economies.

Modelling supply chain risks and their impacts on the performance of the sago starch agro-industry

Purpose

Supply chain risks (SCRs) have uncertainty and interdependency characteristics that must be incorporated into the risk assessment stage of the SCR management framework. This study aims to develop SCR networks and determine the major risk drivers that impact the performance of the sago starch agro-industry (SSA).

Design/methodology/approach

The risk and performance variables were collected from the relevant literature and expert consultations. The Bayesian network (BN) approach was used to model the uncertain and interdependent SCRs. A hybrid method was used to develop the BN structure through the expert’s knowledge acquisitions and the learning algorithm application. Sensitivity analyses were performed to examine the significant risk driver and their related paths.

Findings

The analyses of model indicated several significant risk drivers that could affect the performance of the SSA. These SCR including both operational and disruption risks across sourcing, processing and delivery stage.

Research limitations/implications

The implementation of the methodology was only applied to the Indonesian small-medium size sago starch agro-industry. The generalization of findings is limited to industry characteristics. The modelled system is restricted to inbound, processing and outbound logistics with the risk perspective from the industry point of view.

Practical implications

The results of this study assist the related actors of the sago starch agro-industry in recognizing the major risk drivers and their related paths in impacting the performance measures.

Originality/value

This study proposes the use of a hybrid method in developing SCR networks. This study found the significant risk drivers that impact the performance of the sago starch agro-industry.

Supply risk identification in manufacturing supply networks

Purpose

Managing supply risk is gaining in importance in the tightly interconnected global economy. Identifying the relevant risks is the foundation of any risk management process. Therefore, the purpose of this paper first is to provide a short introduction to supply risk management, before focussing on the identification of such risks in more detail. A holistic framework of the identified supply risks, which distinguishes between risk dimensions and risk factors in manufacturing upstream supply networks, is proposed.

Design/methodology/approach

This study applies a mixed methods research approach. Data are collected based on a structured literature review in combination with the analysis of company-specific documents and semi-structured expert interviews. Subsequently, a deductive content analysis is carried out to derive a holistic framework of supply risks, adapted to the manufacturing industry. For the external validation of the conceptual supply risk framework, additional experts from several manufacturing companies were consulted.

Findings

Based on the definition and delimitation of supply risk, a categorization of supply risks is developed. The relevant literature, as well as expert interviews, lead to the distinction of six supply risk dimensions: quality, delivery, collaboration, economic, ambience and compliance. A total of 27 risk factors can be assigned to these dimensions. A holistic foundation for the management of supply risk is thus created.

Originality/value

This study provides a holistic framework of relevant supply risks in the context of the manufacturing industry. This overview of identified risks offers a novel perspective on risk in manufacturing supply networks that can be helpful in researching assessment and mitigation strategies. Despite the high relevance and popularity of this field of research, such an overview with a focus on manufacturing had not yet been made available in the literature. Building thereon, management approaches can now be developed to handle the risk arising from the upstream of the supply network.

An integrated framework for the assessment of inbound supply risk and prioritization of the risk drivers

Purpose

The purpose of this paper is to present a framework for identifying various inbound supply-risk factors and analyzing its indicators considering the contextual relationship between them. This study additionally proposes a framework for developing an overall inbound supply-risk score considering a real-life case of the electronics supply chain (ESC) in the Indian context.

Design/methodology/approach

In total, 32 risk indicators are identified by a systematic literature review approach and are validated by supply chain practitioners/experts and further categorized into six main risk factors. A hybrid multi-criteria decision-making-based DANP (DEMATEL and ANP) framework is employed to develop the overall inbound-supply-risk score (ISRS) and to prioritize the risk indicators. Indian ESC is chosen as a viable case study to demonstrate the effectiveness of the proposed framework.

Findings

The outcomes from the study reveal that the overall ISRS in the ESC is 36 percent and additionally forewarns critical inbound-supply-risk factors such as supplier performance, product, and buyer organization. Further, the study also identifies the most significant risk indicators such as price margin, investment, on-time delivery, order fulfillment and design changes for ESC.

Research limitations/implications

Supply chain practitioners can adopt this framework as a useful inbound supply-risk assessment tool. Moreover, the hybrid framework will address subjectivity and interrelations among various factors through experts’ judgments. The results will assist the managers to have better insights on the critical risk factors and their complicated interrelationships and further strategize action plans to nullify the impact of incoming risks. This study mainly focused on risk identification and assessment of electronics inbound-supply-risk indicators in the Indian context. The framework can be used for other manufacturing and service industries, albeit the results derived are in the context of a developing country.

Originality/value

This paper provides an effective risk assessment framework for the supply chain practitioners/managers to develop a decision-support system for inbound-supply-risk quantification and prioritization of risk factors in the context of the ESC.