Lucas Baier, Niklas Kühl, Ronny Schüritz and Gerhard Satzger
While the understanding of customer satisfaction is a key success factor for service enterprises, existing elicitation approaches suffer from several drawbacks such as high manual…
Abstract
Purpose
While the understanding of customer satisfaction is a key success factor for service enterprises, existing elicitation approaches suffer from several drawbacks such as high manual effort or delayed availability. However, the rise of analytical methods allows for the automatic and instant analysis of encounter data captured during service delivery in order to identify unsatisfied customers.
Design/methodology/approach
Based on encounter data of 1,584 IT incidents in a real-world service use case, supervised machine learning models to predict unsatisfied customers are trained and evaluated.
Findings
We show that the identification of unsatisfied customers from encounter data is well feasible: via a logistic regression approach, we predict dissatisfied customers already with decent accuracy—a substantial improvement to the current situation of “flying blind”. In addition, we are able to quantify the impacts of key service elements on customer satisfaction.
Research limitations/implications
The possibility to understand the relationship between encounter data and customer satisfaction will offer ample opportunities to evaluate and expand existing service management theories.
Practical implications
Identifying dissatisfied customers from encounter data adds a valuable methodology to customer service management. Detecting unsatisfied customers already during the service encounter enables service providers to immediately address service failures, start recovery actions early and, thus, reduce customer attrition. In addition, providers will gain a deeper understanding of the relevant drivers of customer satisfaction informing future new service development.
Originality/value
This article proposes an extendable data-based approach to predict customer satisfaction in an automated, timely and cost-effective way. With increasing data availability, such AI-based approaches will spread quickly and unlock potential to gain important insights for service management.
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Gustavo Alves de Melo, Maria Gabriela Mendonça Peixoto, Samuel Borges Barbosa, Maria Cristina Angélico Mendonça, Thiago Henrique Nogueira, José Baltazar Salgueirinho Osório de Andrade Guerra, Luiz Gonzaga de Castro Júnior, André Luiz Marques Serrano and Lucas Oliveira Gomes Ferreira
The aim of this study was to evaluate the performance of fuel flow processes in a network of eight gas stations, located in the mesoregion of Alto Paranaíba and Triângulo Mineiro.
Abstract
Purpose
The aim of this study was to evaluate the performance of fuel flow processes in a network of eight gas stations, located in the mesoregion of Alto Paranaíba and Triângulo Mineiro.
Design/methodology/approach
Two multi-criteria decision support methods were applied, respectively, of a statistical and mathematical nature, namely, Principal Component Analysis (PCA) and Data Envelopment Analysis (DEA). The research method used was quantitative, with a brief complement of qualitative research, and descriptive in purpose, supported by the inductive method. The data collection stage took place with the support of interviews, with the application of a structured questionnaire, and non-probabilistic sampling, for convenience.
Findings
It was possible to verify that the gas station that stood out the most was station 2 (GS2), which achieved maximum efficiency, a fact that can be justified by the analysis resulting from the application of PCA, as for the product purchase variable (PP), the GS2 is the one that buys the most fuel, and is also the one with the largest storage capacity (C), and the highest volume of product sales (PS), which suggests signs of balance between supply and demand for this station, justifying its prominence.
Research limitations/implications
The limitations of the study were related to the DEA technique, which requires a number of variables/indicators three times smaller than the number of DMUs considered, and the difficulty in obtaining financial data on the DMUs analyzed. Considering the security and anonymity of the gas station network, it was not possible to use this data.
Practical implications
The performance assessment of fuel flow processes carried out in this study promotes the efficient use of available resources as well as identifying efficient DMUs that represent benchmarks for improving management processes and performance of inefficient DMUs.
Social implications
From a social perspective, this study promotes the improvement of the quality of flow processes and effective management of the fuel supply chain, ensuring the safe storage and transportation of fuels to customer supply. Performance management in this sector moves other sectors of the economy, since an efficient unit represents a balance between supply and demand, and consequently, boosts the regional economy, promoting economic growth of the population. Hiring qualified labor for this purpose also represents one of the implications of the study. From an environmental perspective, optimizing flow processes generates a reduction in greenhouse gas emissions and encourages the formulation of public policies aimed at consolidating sustainable practices.
Originality/value
Performance management applied to the context of the fuel supply chain is a relevant topic that has been little explored in scientific research, with a low level of information detail. This study using the inductive method allows the generalization and replication of this management pattern in other organizations in the sector in order to increase the efficiency of the fuel distribution system, with the perspective of maximizing outputs and reducing input consumption. In this aspect, the study introduces possibilities for advancement in social and environmental perspectives based on the effective management of fuel logistics.
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Edem Kofi Boni and S. Asieh H. Tabaghdehi
The retail industry has experienced significant transformations driven by digitalization and the challenges posed by the COVID-19 pandemic. This chapter aims to explore the impact…
Abstract
The retail industry has experienced significant transformations driven by digitalization and the challenges posed by the COVID-19 pandemic. This chapter aims to explore the impact of digitalization on retail business models and understand consumer purchasing habits during emergencies. This chapter will examine the influence of scarcity and competitive arousal on consumer choices, the effects of stock-outs on brand and store preferences, price sensitivity, waiting times and the shift towards online shopping. Additionally, it will address concerns about social exclusion in digital channels and the potential for bridging the gap between offline and online shopping experiences.
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Kathryn H. Dekas and Wayne E. Baker
A work orientation represents a person’s beliefs about the meaning of work – the function work plays in the person’s life and the constellation of values and assumptions the…
Abstract
Purpose
A work orientation represents a person’s beliefs about the meaning of work – the function work plays in the person’s life and the constellation of values and assumptions the person holds about the work domain. Research has suggested that adults tend to favor one of three primary work orientations: job, career, or calling. Empirical studies have shown that adults with different primary work orientations tend to experience different work and career outcomes; however, scholars have not analyzed how or why an individual first develops a work orientation. In this study, we take a first step toward investigating the origins of adults’ work orientations.
Design/methodology/approach
We propose hypotheses drawing on extant literature on the development of work values and occupational inheritance. We test hypotheses using a retrospective research design and survey methodology, with a sample of working adults.
Findings
Work orientations are developed through socialization processes with parents during adolescence. There are different patterns of development across the three work orientation categories: stronger calling orientations are developed when both parents possess strong calling orientations; stronger career orientations develop in accordance with fathers’ career orientations; and job orientations are related more to the nature of the adolescent’s relationship with parents than with parents’ own work orientations.
Originality/value
This research provides the first empirical study of the origin and development of work orientations.
Research limitations/implications
This research offers insight into ways generations are connected through the perceived meaning of their work, even as the nature of work changes. We encourage future scholars to use this as a starting point for research on the development of work orientations, and to continue exploring these questions using additional methods, particularly longitudinal study designs.
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Ashikul Kabir, Saiyara Shabbir Ikra, Paolo Saona and Md. Abul Kalam Azad
This study extends the current literature in the context of European countries by showing that women's participation on the board can enhance the financial performance of a…
Abstract
Purpose
This study extends the current literature in the context of European countries by showing that women's participation on the board can enhance the financial performance of a company while moderated by many cultural factors.
Design/methodology/approach
This study examines 19 European countries throughout the period 2010–2020. The time-invariant or individual fixed-effect models are used.
Findings
The authors found that high power distance and masculinity undermine the impact of board gender diversity on firm performance. The gender-diverse board reports a statistically significant negative impact on return on asset (ROA) and return on equity (ROE) while moderated by the power distance index.
Originality/value
This research will be of significant value to the board directors, practitioners and the concerned authority who desire to polish up the firm performance of European countries that are governed by cultural norms.
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Davide Luzzini, Federico Caniato, Stefano Ronchi and Gianluca Spina
The purpose of this paper is to propose a theoretically sound and empirically tested classification system composed of purchasing strategic categories as a basis for purchasing…
Abstract
Purpose
The purpose of this paper is to propose a theoretically sound and empirically tested classification system composed of purchasing strategic categories as a basis for purchasing portfolio models.
Design/methodology/approach
An international, cross‐industry survey has been designed to assess the characteristics and corresponding strategies of the purchasing categories.
Findings
The paper operationalises the constructs derived from previous scientific contributions related to purchasing portfolio management and transaction cost economics (TCE) to empirically test the purchasing portfolio. In total, four different types of strategic categories have been identified, and distinctive competitive priorities have been found.
Research limitations/implications
Managers might be able to identify different types of purchasing strategic categories, whose characteristics drive specific purchasing strategies. Longitudinal data and more extensive tests of the characteristics of each category might contribute to improving the proposed research framework.
Originality/value
The research overcomes some of the classical limits of purchasing portfolio models, including the absence of a theoretical and empirical basis. In particular, TCE is used to support and expand traditional purchasing portfolio approaches, and a broad empirical base is used to test such an approach.
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Dongping Cao, Xuejiao Teng, Yanyu Chen, Dan Tan and Guangbin Wang
This study aims to explore how project-based firms, which generally organize most of their work around temporary projects in discontinuous and fragmented types of business…
Abstract
Purpose
This study aims to explore how project-based firms, which generally organize most of their work around temporary projects in discontinuous and fragmented types of business contexts, proactively formulate and implement digital transformation strategies under institutional pressures in a predigital era.
Design/methodology/approach
An exploratory case study was conducted in a large-scale construction company in China using multiple data collection methods, including semistructured interviews, documentation collection and observation.
Findings
An integrated framework is developed to conceptualize three key dimensions of digital transformation strategies of project-based firms: strategic adaptation for organization-environment fit through balancing the internal efficiency needs with the external legitimacy pressures; proactive business transformation through comprehensively managing the roles of digital technologies in optimizing defined business processes and fostering new business models; and delicate organizational transformation to integrate temporary project-level operation processes with ongoing firm-level business processes.
Originality/value
This study represents an exploratory effort to empirically investigate how project-based firms strategically organize complex digital transformation imperatives in their discontinuous and fragmented business contexts. The findings contribute to deepened understandings of how complex organizational and environmental contexts can be comprehensively managed for systemic business and organizational transformations to leverage the value of emerging digital technologies for project-based organizations.