Supply chain quality risk management: an empirical study of its dimensions and impact on firm performance

The goal of this dissertation is to understand what supply chain quality risk management (SCQRM) is and how SCQRM can help firms improve product quality and firm performance. This dissertation attempts to reveal and understand the SCQRM practices in order to provide new insights in dealing with supply chain quality risk. Thus, this dissertation aims to address three research questions: RQI) What should SCQRM entail in order to reduce the risk to the quality of products being handled along the supply chain? RQ2) What would a valid measurement scale of SCQRM entail? RQ3) What is the impact of SCQRM on product quality and firm's performance? In this research, a comprehensive SCQRM framework is proposed. SCQRM is conceptualised as a multidimensional, second-order construct that is represented by a system of four interrelated and complementary dimensions: risk shifting, risk sharing, risk avoidance, and risk remedy. These four SCQRM dimensions are subsequently examined in the conceptual model in relation to performance, and three key approaches are adopted: (a) statistical analysis to validate the measurement instrument of SCQRM; (b) measurement model analysis technique to investigate multi-dimensionality of SCQRM; (c) structural model building technique to examine the relationships between SCQRM dimensions and performance. In such, quantitative analysis techniques, exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modelling (SEM), are adopted to analyse survey data from 289 companies. Three contributions to knowledge are made in advancing the literature of SCQRM. Firstly, this study reports a 7-stage procedure for developing a reliable and valid measure of SCQRM. Secondly, the measure of SCQRM is found to be a multidimensional construct consisting of four unique dimensions. Thirdly, this study examines the significant positive effect of the complementarity system of SCQRM on product quality and on firm performances. Moreover, the findings imply that a successful SCQRM results from building a complementarity power in risk management resources and routines. The multiple manifestations of the four SCQRM dimensions are all driven by a cohesive, yet unobserved synergy, which also forms one of the competences of the firm. Moreover, the managerial implication suggests that complementary benefits arise from the adoption of a more holistic approach to the management of supply chain quality risk at the firm-level

Supply chain quality risk management: an empirical study of its dimensions and impact on firm performance

The goal of this dissertation is to understand what supply chain quality risk management (SCQRM) is and how SCQRM can help firms improve product quality and firm performance. This dissertation attempts to reveal and understand the SCQRM practices in order to provide new insights in dealing with supply chain quality risk. Thus, this dissertation aims to address three research questions: RQI) What should SCQRM entail in order to reduce the risk to the quality of products being handled along the supply chain? RQ2) What would a valid measurement scale of SCQRM entail? RQ3) What is the impact of SCQRM on product quality and firm's performance? In this research, a comprehensive SCQRM framework is proposed. SCQRM is conceptualised as a multidimensional, second-order construct that is represented by a system of four interrelated and complementary dimensions: risk shifting, risk sharing, risk avoidance, and risk remedy. These four SCQRM dimensions are subsequently examined in the conceptual model in relation to performance, and three key approaches are adopted: (a) statistical analysis to validate the measurement instrument of SCQRM; (b) measurement model analysis technique to investigate multi-dimensionality of SCQRM; (c) structural model building technique to examine the relationships between SCQRM dimensions and performance. In such, quantitative analysis techniques, exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modelling (SEM), are adopted to analyse survey data from 289 companies. Three contributions to knowledge are made in advancing the literature of SCQRM. Firstly, this study reports a 7-stage procedure for developing a reliable and valid measure of SCQRM. Secondly, the measure of SCQRM is found to be a multidimensional construct consisting of four unique dimensions. Thirdly, this study examines the significant positive effect of the complementarity system of SCQRM on product quality and on firm performances. Moreover, the findings imply that a successful SCQRM results from building a complementarity power in risk management resources and routines. The multiple manifestations of the four SCQRM dimensions are all driven by a cohesive, yet unobserved synergy, which also forms one of the competences of the firm. Moreover, the managerial implication suggests that complementary benefits arise from the adoption of a more holistic approach to the management of supply chain quality risk at the firm-level

Investment performance analysis of industrial products: case of an effluent processing facility at a chemical company

This paper proposes an approach to a multi-criteria investment performance analysis of industrial products. Manufacturers must determine the necessary and sufficient specification of products they use. Such an analysis, however, involves a broad range of factors, including some that are subjective. The performance analysis and decision making for investment thus must often rely heavily on past experience, generalities, and intuition. This paper addresses these issues from a benefit, opportunity, cost and risk (BOCR) perspective, in which the criteria are prioritized and the products are evaluated objectively. Pairwise comparisons among the criteria and quantitative assessments of the performance of products comprise a prioritized BOCR analysis. A case study demonstrating the applicability of the proposed approach is conducted at a chemical company. Results show that the proposed approach succeeds in the multi-criteria performance analysis of industrial products, resulting in a practical proposal of a product specification best suited to this company’s case

Exploring the Public Perception in Social Big Data: An Investigation in Mars Recall Scandal

Social media has become a popular platform of interpersonal communication in which users can search for news and convey real-time information. Researching into social big data, such as Twitter, can be an effective way to identify public opinions and feelings in risk emergence, as it provides rich sources of data for opinion mining and sentiment analysis. This study aims to investigate and analyse the public perception towards the Mars and Snickers product recall scandal. The study proposes a comprehensive data analysis framework, and utilises the dataset formed of 10,930 Twitter messages over the span of 10-day following the product recall announcement made by Mars Inc., to gauge public attitudes and opinions. The study finds that the overall attitude of Twitter users towards the scandal was negative, and Snickers were the most mentioned product in the 10-day periods after the announcement of the recall. The data analysis highlights that the Tweet diffusion (retweeting) has positive associations with the number of followers and the use of hashtags, hence companies should pay more attention to users who have a large number of followers, as their tweets will be read by a great number of other Twitter users. The findings suggest effective methods for practitioners in crisis management (e.g., how to use social media to disseminate information). The study also presents a progressive tweet-mining framework that can serve as a tool in crisis management to classify the tweet topics, identify and analyse the sentiment and comprehend the changes of the public attitudes

The Effects of Risk and Reward Sharing on Quality Performance

Purpose: Firms face critical challenges in managing product quality in a global supply chain. In many cases, these challenges could be regarded as an agency problem which is a result of the goal conflict between the supply chain members. To address such agency problem, the purpose of this paper is twofold: first, to explain how risk and reward sharing practices contribute to firms’ quality performance in the supply chain; and second, to identify the drivers of applying risk and reward sharing. Design/methodology/approach: The hypothesised model, based on agency theory, is empirically verified by original survey data of 200 Chinese manufacturing companies using the structural equations modelling approach in a context of product recall. Findings: Supplier involvement and task programmability are two significant antecedents of risk and reward sharing. Further, the paper shows that risk and reward sharing have a positive effect on quality performance, however, in terms of contribution to quality performance, risk sharing and reward sharing may be substitution practices. Practical implications: This research explains how managers could embrace better preparedness for risk and reward sharing in their supply chains. It is also suggested that although risk and reward sharing are seen as efficient means to improve quality performance, such practices should not be treated as a bundle. Originality/value: Building on supply partnership literature, this paper contributes to agency theory by providing a solution to the agency problem, i.e., risk and reward sharing and adding to the limited understanding of the antecedents of risk and reward sharing and examining the effects of risk and reward sharing on quality performance

Data-driven and adaptive leadership contributing to sustainability: global agri-food supply chains connected with emerging markets

Despite numerous promises on the links between data-driven and adaptive leadership, non-financial sustainability and financial sustainability, scholars have not conducted enough empirical research to test the links based on globally and massively connected emerging supply chains. This study therefore scrutinizes the interlocking links by applying the data collected from chief executive officers, managing directors and senior operations managers of such supply chains rooted in emerging markets. The possibly purified results raised from structural equation modeling indicate that data-driven and adaptive leadership is a key determinant for non-financial sustainability, which in turn contributes to financial sustainability. Directly, the leadership also plays a vital role for financial sustainability. Interaction effects further depict that the companies which apply more data-driven and adaptive leadership practices perform better compared to those which less focus on such practices. Consequently, the results provide the deeper understanding of the mechanism of how global supply chain leaders can use data-driven and adaptive leadership to co-create financial and non-financial sustainability

Unleashing the power of supply chain learning: an empirical investigation

Purpose Organisational learning plays a critical role for firms to keep abreast of a supply chain environment filled with volatility, uncertainty, complexity and ambiguity (VUCA). This study investigates the extent to which supply chain learning (SCL) affects operational resilience under such circumstances. Design/methodology/approach This study developed a research framework and underlying hypotheses based on SCL and information processing theory (IPT). An empirical test was carried out using secondary data derived from the “Supply Chain Policy” launched by the Chinese government and two large related conferences. Findings SCL positively relates to operational resilience, and several moderators influence the relationship between them. The authors argue that digital-technological diversity could weaken the role of SCL in operational resilience, whereas customer concentration, and participating in a pilot programme could enhance the effect of SCL. Practical implications Firms should embrace the power of SCL in building resilience in the VUCA era. Meanwhile, they should be cautious of a digital-technological diversification strategy, appraise the customer base profile and proactively engage in pilot programmes. Originality/value This research develops the SCL construct further in the context of China and empirically measures its power on operational resilience using a unique dataset. This contributes to the theorisation of SCL

Analysing online reviews to investigate customer behaviour in the sharing economy: The case of Airbnb

Purpose: The purpose of this paper is to investigate attributes that influence Airbnb customer experience by analysing online reviews from users staying in London. It presents a text mining approach to identify a set of broad themes from the textual reviews. It aims to highlight the customers’ changing perception of good quality of accommodations. Design/methodology/approach: This paper analyses 169,666 reviews posted by Airbnb users who stayed in London from 2011 to 2015. Hierarchical clustering algorithms are used to group similar words into clusters based on their co-occurrence. Longitudinal analysis and seasonal analysis are conducted for a more coherent understanding of the Airbnb customer behaviour. Findings: This paper provides empirical insights about how Airbnb users’ mindset of good quality of accommodations changes over a five-year timespan and in different seasons. While there are common attributes considered important throughout the years, exclusive attributes are discovered in particular years and seasons. Research limitations/implications: This paper is confined to Airbnb experiences in London. Researchers are encouraged to apply the proposed methodology to investigate Airbnb experiences in other cities and detect any change in customer perception of quality stay. Practical implications: This paper offers implications for the prioritisation of customer concerns to design and improve services offerings and for alignment of services with customer expectations in the sharing economy. Originality/value: This paper fulfils an identified need to examine the change in customer expectation across the timespan and seasons in the case of Airbnb. It also contributes by illustrating how big data can be used to uncover key attributes that facilitate the engagement with the sharing economy

Unbundling the W’s: the interface between organisational crises, social media narratives, and image repair strategies

Organisations are susceptible and vulnerable to crisis situations. These organisations have been able to exert resilience, and manage reputational damage, through crisis management protocols that include stakeholder engagement. However, given the rise of social media, a new cohort of stakeholders has emerged. Organisations are therefore faced with the task of managing new stakeholder relationships. This paper applies recent advancements in social media and crisis management discourse to investigate the prevalence of new, undiscovered stakeholders in crisis communications surrounding six prominent crisis situations. The results indicate that online stakeholders are becoming more powerful, urgent and legitimacy; thus shifting dynamics