Benchmarking supplier risks using Bayesian networks

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.

Identifying the key areas for benchmarking towards the improvement of small and medium scale enterprises (SMEs) construction firms in developing countries: the case of Ghana

Purpose

The purpose of this study was to identify key areas for benchmarking (BM) towards the improvement of small and medium scale enterprises (SMEs) construction firms in developing countries.

Design/methodology/approach

The study employed the use of the quantitative research method in the collection and analysis of primary data collected from field surveys using a piloted close-ended questionnaire created following a review of available literature on BM. Based on 63 solicited views of professionals with SMEs (quantity surveyors, project managers and architects) data collected were statistically analysed using a one-sample t-test.

Findings

The findings of the study indicate that the key areas for BM towards the improvement of SME construction firms in developing countries in order of relevance are “Financial Performance”, “Competitiveness”, “Customer Satisfaction”, “Technology Advancement”, “Communication Skills”, “Collaboration”, “Employee Satisfaction” and “Product orientation”.

Practical implications

The study has given more insight into the areas that need more attention for SMEs BM to achieve improvement. It can therefore be suggested firms that adapted identified areas will derive the benefits of BM. It is further opined that more BM education should be provided to various SMEs construction firms to facilitate an effective and efficient BM regime aiming at performance enhancement in project delivery.

Originality/value

This forging research attempts to identify the key areas for BM towards the improvement of SMEs construction firms in developing countries. Although there have been several efforts to create BM tools for the construction industry.

Leveraging a Bayesian network approach to model and analyze supplier vulnerability to severe weather risk: A case study of the U.S. pharmaceutical supply chain following Hurricane Maria

The United States government has identified the health care sector as part of the critical infrastructure for homeland security to protect citizens against health risks arising from terrorism, natural disasters, and epidemics. Citizens also have expectations about the role that health care plays in enjoying a good quality of life, by providing response systems to handle emergencies and other illness situations adequately. Among the systems required to supportdesired performance levels is a robust and resilient pharmaceutical supply chain that is free of disruption. Shortages of drugs place undue pressure on healthcare providers to devise alternative approaches to administer patient care. With climate change expected to result in increasingly severe weather patterns in the future, it is critical that logistics engineers understand the impact that a catastrophic weather event could have on supply chain disruption to facilitate the design of supply systems that are robust and resilient. This study investigates the main causal and intermediate events that led to risk propagation in, and disruption of, the U.S. pharmaceutical supply chain following Hurricane Maria. A causality Bayesian model is developed to depict linkages between risk events and quantify the associated cumulative risk. The quantification is further examined through different advanced techniques such as predictive inference reasoning and sensitivity analysis. The general interpretation of these analyses suggests that port resilience is imperative to pharmaceutical supply chain performance in the case of Puerto Rico.

Product deletion and supply chain repercussions: risk management using FMEA

Purpose

Product portfolio management is a strategic concern. Product portfolio management includes decisions associated with adding new products, maintaining existing products and deleting or phasing out problematic products. This paper first introduces a framework to identify risks of product deletion along supply chain activities. It utilizes failure mode and effects analysis (FMEA) to identify, analyse and evaluate product deletion risks on supply chains and proposes managerial implications for risk management in dynamic business scenarios. It is meant to build upon and address a gap in the product deletion and supply chain linkage literature.

Design/methodology/approach

FMEA is utilized in this study to structure and manage potential risks in product deletion decision-making on supply chains. FMEA is based on an analysis of severity, occurrence and detectability of failure modes. FMEA provides methods to help identify managerial preventive solutions to avoid and mitigate risk consequences of such decisions.

Findings

Ten top product deletion risks are identified in this study; discussions of their negative impact on supply chain performance, and possible managerial recommendations are followed for risk control, monitor and elimination.

Practical implications

Findings help managers to predict, avoid and mitigate risk consequences of product deletion decisions; especially those related to the supply chain. A framework to structure various risks of product deletion in the supply chain can be useful to both practitioners and researchers.

Originality/value

This study advances product portfolio management through enhanced understanding of product deletion decision-making in organizations; and especially contributes to a broader investigation of such decisions in supply chain management. It also structures the factors that play a role in identifying risks.

Artificial Intelligence Based Commercial Risk Management Framework for SMEs

Risk management in commercial processes is among the most important procedures affecting the competitiveness of small and medium-sized enterprises (SMEs), their innovativeness and potential contribution to global sustainable development goals (SDGs). The ecosystem of commercial processes is the prerequisite to manage risk faced by SMEs. Commercial risk assessment and management using elements of artificial intelligence, big data, and machine learning technologies could be developed and maintained as external services for a group of SMEs allowing to share costs and benefits. This paper aims to provide a conceptual framework of commercial risk assessment and management solution based on elements of artificial intelligence. This conceptualization is done on the background of scientific literature, policy documents, and risk management standards. Main building blocks of the framework in terms of commercial risk categories, data sources and workflow phases are presented in the article. Business companies, state policy, and academic research focused recommendations on the further development of the framework and its implementation are elaborated.

Benchmarking supplier external risk factors in electronic equipment industry supply chains

Purpose

The global electronic equipment industry has evolved into one of the most innovative technology-based business sectors to transpire in the last three decades. Much of its success has been attributed to effective supply chain management. The purpose of this paper is to provide an examination of external risk factors associated with the industry’s key suppliers through the creation of Bayesian networks which can be used to benchmark external risks among these suppliers.

Design/methodology/approach

The study sample consists of the suppliers to seven of the leading global electronic equipment companies. Bayesian networks are used as a methodology for examining the supplier external risk profiles of the study sample.

Findings

The results of this study show that Bayesian networks can be effectively used to assist managers in making decisions regarding current and prospective suppliers with respect to their potential impact on supply chains as illustrated through their corresponding external risk profiles.

Research limitations/implications

A limitation to the use of Bayesian networks for modeling external risk profiles is the proper identification of risk events and risk categories that can impact a supply chain.

Practical implications

The methodology used in this study can be adopted by managers to assist them in making decisions regarding current or prospective suppliers vis-à-vis their corresponding external risk profiles.

Originality/value

As part of a comprehensive supplier risk management program, companies along with their suppliers can develop specific strategies and tactics to minimize the effects of supply chain external risk events.

Development of questionnaire to assess the supplier evaluation criteria and supplier selection benefits

Purpose

The purpose of this paper is to develop an instrument/questionnaire to assess the supplier evaluation (SE) criteria and supplier selection (SS) benefits with their level of importance.

Design/methodology/approach

This paper develops an instrument/questionnaire based on generally accepted principle of instrument design to assess the SE criteria and SS benefits through the responses collected from 34 automobile industries in India. The SE criteria and SS benefits were derived through extensive literature review and expert’s opinion.

Findings

The reliability, normality and validity of developed instrument/questionnaire were determined through the responses collected from the managers of 34 automobile industries in India and are found to be acceptable for most of the SE criteria and SS benefits. The criterion validity is also found to be fairly good for the developed instrument/questionnaire.

Research limitations/implications

While designing the instrument/questionnaire, SE criteria and SS benefits were considered for automobile sector in India through prequestionnaire sheet. Further, research may be required to corroborate these results from larger data sets.

Practical implications

Now a days, it is essential for organizations to rely on their suppliers for their survival and to gain competitive advantage. The well developed and validated instrument/questionnaire can be used for industry practitioners in Indian automobile industries to assess the SE criteria and SS benefits.

Originality/value

An empirically tested instrument/questionnaire is developed first time to assess the SE criteria and SS benefits for automobile sector in India.

Risk analysis and mitigation for perishable food supply chain: a case of dairy industry

Purpose

The purpose of this paper is to present a methodology to analyze the risks present in perishable food supply chain and to determine the most effective risk mitigation strategies. It is achieved by understanding the dynamics between various risks in perishable food supply chain and modeling them using interpretive structural modeling (ISM).

Design/methodology/approach

Four categories and 17 types of risk are established from literature and conducting brainstorming sessions with managers/engineers in Indian dairy firms. A methodology is proposed using ISM, risk priority number and risk mitigation number to prioritize risk mitigation strategy decisions for the dairy industry.

Findings

For a perishable food supply chain, risk positioned at lower levels (levels 1 or 2) in the hierarchy should be targeted first, while formulating mitigation strategies. To investigate further, risk- enabling factors which are identified for an Indian dairy firm for these levels 1 and 2 risks and mitigation strategy prioritization show that supplier side risks are more dominant followed by market risks and process risks.

Research limitations/implications

This proposed methodology has not been statistically validated or empirically tested, and factors taken are in the Indian context, but the authors believe that the study is highly relevant to other markets as well because the ISM-based analysis is for generic perishable food supply chain environment.

Practical implications

This study provides a useful approach to managers/decision makers to identify, analyze and prioritize risk in the supply chain. It also provides insights into the mutual relationships of supply chain risks which would help them to focus on the effective risk mitigation strategies formulation. The study provides the insights to benchmark and risk management in the dairy industry environment with priority considerations.

Originality/value

This paper provides an integrated approach to identifying, quantify, analyze, evaluate and mitigate the risks of perishable food (in the dairy environment) in the Indian context.

A methodology for analyzing shipyard supply chains and supplier selection

Purpose

– The purpose of this paper is to focus on shipyard supply chains in order to identify the processes that take place and evaluate the risks associated with suppliers.

Design/methodology/approach

– For this analysis two methodologies are applied. The first is the understand, document, simplify, optimize, where the first two steps are used for analysing the processes and the documentation of the best practices, which take place in the daily operations. The second tool is Kraljic’s matrix, which is applied for the identification of supplier selection and associated risks.

Findings

– The analysis shows that strategic co-operations between shipyards suppliers are essential for improved supply chain performance since supplier improvement in terms of lead times and product quality are achieved. It is also seen that the shipyard supply chain performance can be improved by adjusting the best practices to the needs dictated each time by the project’s specifications.

Practical implications

– The findings provide valuable insights for practitioners, as well as academicians, policy makers and also integrate supplier selection under the supply chain. Managers can acquire reliable information about those suppliers who exhibit best practice.

Originality/value

– A number of key processes and best practices have been identified, which are essential for the upstream and downstream coordination of the shipyard supply chain. The present work is an approach to evaluating the risks associated with the shipyard’s suppliers and assists in benchmarking their risk profile.

An investigation of lead benchmarking implementation

Purpose

– The purpose of this paper is to explore current levels of lead benchmarking implementation and lead performance indicators among Malaysian organizations. Comparing small and medium enterprises (SMEs) with large companies, it identifies what benefits and difficulties are present during benchmarking implementation.

Design/methodology/approach

– Descriptive analyses, one-way ANOVAs between and within groups, and parametric and non-parametric tests are used to compare responses obtained from small, medium and large Malaysian manufacturing organizations.

Findings

– Findings suggest that larger organizations have a more progressive approach to lead benchmarking. Strategy and employee development are dominant lead performance indicators of continuous improvement. Large companies experience fewer challenges when implementing benchmarking projects. Perceptions of key benchmarking implementation barriers shift from mere lack of resources toward lack of knowledge and training, information sharing, commitment and trust.

Research limitations/implications

– The sample is specific in nature (Malaysian manufacturing organizations); results should be interpreted accordingly.

Originality/value

– Little is known about lead benchmarking practices in Malaysia, particularly within the contexts of SMEs. The outcomes of this study provide a basis for further improvement and valuable knowledge for top management of manufacturing organizations to refine strategies and advance quality management approaches.