Search results

The purpose of this study is to develop and test a new customer satisfaction index model for Turkish mobile phone sector (TMPS).

Based on relevant literature and theoretical considerations on customer satisfaction, a new measurement model was developed. A survey based on the proposed model was conducted to 700 mobile phone users in Istanbul. Partial least squares method was employed to estimate the proposed structural equation model (SEM).

The general applicability of a SEM depends on the reliability and validity of the modeling results. The proposed satisfaction model exhibits strong explanatory power with its satisfactory reliability and validity results.

The proposed model was tested for the TMPS. It should ideally be tested periodically for different sectors with more data, and the index results should be compared.

The results of this study provide very important information for the managers in formulating competitive marketing strategies. The results show the critical points where the limited resources of the firms should be allocated to improve satisfaction and loyalty. Independent and uniform measurement characteristics of the studied model provide a useful tool for tracking performance and systematic benchmarking over time. It also provides information about the weaknesses and strengths of the company from the eyes of its customers.

This study is an attempt to develop and implement a satisfaction model for the TMPS. The proposed model consists of well‐established theories and approaches in customer behavior.

The purpose of this paper is to demonstrate the use of two general purpose decision‐making techniques in selecting the most appropriate maintenance strategy for organizations with critical production requirements.

The Analytical Hierarchical Process (AHP) and the Analytical Network Process (ANP) are used for the selection of the most appropriate maintenance strategy in a local newspaper printing facility in Turkey.

The two methods were shown to be effective in choosing a strategy for maintaining the printing machines. The two methods resulted in almost the same results. Both methods take into account the specific requirements of the organization through its own available expertise.

The techniques demonstrated in this paper can be used by all types of organizations for selecting and adopting maintenance strategies that have higher impact on maintenance performance and hence overall business productivity. The two methods are explained in a step‐by‐step approach for easier adaptation by practitioners in all types of organizations.

The value of the paper is in applying AHP and ANP decision‐making methodologies in maintenance strategy selection. These two methods are not very common in the area of maintenance, and hence add to the pool of techniques utilized in selecting maintenance strategies.

This study aimed to design a user-participatory methodology to investigate the post-occupancy sustainability of reused historical buildings and to apply it to a case study.

This study was designed in four stages. In the first stage, the sustainability parameters and sub-parameters were determined in the reused historical buildings based on the literature. The second stage included a field study in which the current situation of the study area was analysed, and the users were reached using the survey technique. In the third stage, the data obtained from the user participation were analysed with importance performance analysis (IPA) and an IPA matrix was created. The fourth stage included an evaluation of the results of the analysis and the development of recommendations.

IPA is a supportive method for ensuring the sustainable use of historic buildings. According to the data obtained from the IPA, it was seen that the functional sustainability of the building was achieved to a great extent. At the same time, there were deficiencies in technical and environmental sustainability. In terms of aesthetic sustainability, it was observed that the importance and performance values given by the users were generally consistent with each other.

The originality of this study is that the performance of the reused historical buildings in the process of use was monitored with appropriate parameters, and a user-participated method was proposed that allows improvement suggestions to be developed in line with the results obtained.

This paper aims to examine how socio-economic status (SES) shapes consumers’ purchase behavior of genuine brands and counterfeits. It also forms a typology based on the decision-making processes of these two groups by exploring neutralization processes and emotional outcomes related to their behaviors.

Data are collected through in-depth, semi-structured interviews with 42 users and non-users of counterfeits from different SES groups.

This paper develops a consumer typology based on the customer behavior of counterfeit and genuine brand users, as well as emotional outcomes and neutralization strategies used to justify their actions according to their SES group. These categories are defined as the black chameleons, the counterfeit owners, the genuine brand owners and the authenticity seekers.

This paper contributes to the counterfeit literature by examining the consumption practices of each SES group of users and non-users of counterfeits by focusing on motivations, emotional outcomes and neutralization processes. The study shows how consumers’ end consumption practices and their SES group explains the mix findings on the counterfeit literature.

Despite several advantages of Building Information Modelling (BIM) technology, BIM has not been adopted and implemented extensively in developing countries. Consequently BIM remains at a beginner level in developing countries. To increase the level of BIM implementation, first, knowing the root factors that resist BIM implementation is necessary to know. Therefore, the objective of this study was to identify the factors that limit BIM implementation in developing countries, specifically in the Turkish Architecture, Engineering and Construction (AEC) industry.

A questionnaire was designed with 46 influencing causes (ICs) identified through a systematic literature review. In total, 141 survey results were returned from architects and engineers, and reliability analysis, exploratory factor analysis, and confirmatory factor analysis were conducted. Furthermore, a structural equation model (SEM) was developed to identify the root factors of BIM implementation.

Eight root factors affecting the prevalent use of BIM technology in the Turkish construction industry were determined and grouped into three categories based on BIM implementation level. Problems with the BIM transition process and a lack of management support are the most influential root factors limiting BIM implementation. Lack of incentives, lack of BIM education, bias regarding BIM technology and BIM-based software problems form the second group of root factors that have a significant effect. Awareness and lack of communication amongst stakeholders were identified as root factors that had a moderate effect.

This study contributes to the knowledge body by revealing eight root factors limiting BIM implementation in the Turkish AEC industry which can be generalised to most developing countries. Therefore, the outcomes of this study may be used as a practical reference for future research aimed at improving BIM adoption in developing countries through governmental, educational, and managerial solutions.

Several studies have identified the challenges and barriers of BIM implementation in the construction industry using qualitative and quantitative analyses and projected the current state. Unlike previous studies, this study comprehensively and quantitatively determined the root factors that constrain the use of BIM in Turkey using exploratory factor analysis, confirmatory factor analysis, and structural equation modelling to present a structural model.

This paper aims to study the factors that influence customer loyalty toward the internet service providers in Malaysia. The five factors used are corporate image, perceived quality, perceived value, price fairness and promotion. The mediating variable of this study is customer satisfaction, while customer loyalty is the study variable.

The primary data collection has been done by distributing survey questionnaires to 338 internet users in Malaysia. The data collected have been analyzed with SAS software.

The results showed that perceived quality has the strongest influence on customer satisfaction toward internet service providers in Malaysia. However, corporate image has no relationship with customer satisfaction toward internet service providers in Malaysia. Furthermore, customer satisfaction has a significant and positive relationship to customer loyalty toward the internet service providers in Malaysia.

European Customer Satisfaction Index has been adopted and combined with price fairness and promotion as a new research model that other researchers may look into it further. This research may also serve as a guide to internet service providers as they may learn about the underlying factors that affect the satisfaction and loyalty of customers and which factor has the strongest impact.

Partial least squares structural equation modeling (PLS-SEM) has become popular in the information systems (IS) field for modeling structural relationships between latent variables as measured by manifest variables. However, while researchers using PLS-SEM routinely stress the causal-predictive nature of their analyses, the model evaluation assessment relies exclusively on criteria designed to assess the path model's explanatory power. To take full advantage of the purpose of causal prediction in PLS-SEM, it is imperative for researchers to comprehend the efficacy of various quality criteria, such as traditional PLS-SEM criteria, model fit, PLSpredict, cross-validated predictive ability test (CVPAT) and model selection criteria.

A systematic review was conducted to understand empirical studies employing the use of the causal prediction criteria available for PLS-SEM in the database of Industrial Management and Data Systems (IMDS) and Management Information Systems Quarterly (MISQ). Furthermore, this study discusses the details of each of the procedures for the causal prediction criteria available for PLS-SEM, as well as how these criteria should be interpreted. While the focus of the paper is on demystifying the role of causal prediction modeling in PLS-SEM, the overarching aim is to compare the performance of different quality criteria and to select the appropriate causal-predictive model from a cohort of competing models in the IS field.

The study found that the traditional PLS-SEM criteria (goodness of fit (GoF) by Tenenhaus, R2 and Q2) and model fit have difficulty determining the appropriate causal-predictive model. In contrast, PLSpredict, CVPAT and model selection criteria (i.e. Bayesian information criterion (BIC), BIC weight, Geweke–Meese criterion (GM), GM weight, HQ and HQC) were found to outperform the traditional criteria in determining the appropriate causal-predictive model, because these criteria provided both in-sample and out-of-sample predictions in PLS-SEM.

This research substantiates the use of the PLSpredict, CVPAT and the model selection criteria (i.e. BIC, BIC weight, GM, GM weight, HQ and HQC). It provides IS researchers and practitioners with the knowledge they need to properly assess, report on and interpret PLS-SEM results when the goal is only causal prediction, thereby contributing to safeguarding the goal of using PLS-SEM in IS studies.

This study aims to establish a rigorous model that can pragmatically evaluate the facilities management (FM) performance of hospitals.

Among the applicable performance indicators that were identified from extant literature, a focus group study shortlisted ten key performance indicators (KPIs) in four categories (safety, physical, financial and environmental) and verified their practicality. Using the analytic network process (ANP) method to process the focus group’s responses yielded importance weightings for the KPIs and developed the intended evaluation model. This model was then validated by a case study.

From the empirical data collected, two types of FM performance data and two scenarios of KPI scores were identified. To process these data and scores, a robust calculation method was devised and then proved useful in obtaining an overall score for holistic hospital FM performance. The case study confirmed the appropriateness and validity of the model developed.

Through illustrating how the ANP method could be applied to develop an FM performance evaluation model, the study contributes knowledge to the multi-criteria decision-making domain. Despite the geographical limitation of the model established (i.e. centered around a group of hospitals investigated in Hong Kong), the study can serve as a reference for developing performance evaluation models for other buildings or infrastructures globally.

The model constitutes a practical tool for evaluating the FM performance of hospitals. Using this model on a regular basis will enable performance benchmarking and hence, continuous improvement of FM services.

The ANP model established is the first of its kind tailored for evaluation of hospital FM performance.

Heightened public concerns for the global environment due to human overexploitation have given rise to many green product initiatives by businesses. Green cosmetics (GC) are products developed and marketed based on ecological sustainability and have shown increasing consumer appeal worldwide. The current research investigates the antecedents of green cosmetics consumption among Indian GC users, hitherto un-investigated comprehensively.

The study is a cross-sectional pairwise comparison of green evaluation criteria for cosmetics using an expert panel of thirty Indian cosmetic users using a fuzzy analytic hierarchy process (F-AHP) and investigate the impact of a comprehensive list of antecedents on the multi-criteria category consumption decision.

The study results indicate that perceived consumer effectiveness is the most critical factor for green cosmetics consumption in India, followed by brand trust, behavioural control, and environmental effectiveness. The least important factors are price and social norms.

As the GC category is at nascent stage in India the investigation is limited to the GC category innovators – a set of people high in intellectual and financial resources. The study is also limited to women users as the male cosmetic market in the country is still very small.

The study results can help marketers in designing and implementing GC related marketing strategies to deliver higher customer value to the target segment. Academicians can use the study results for better prediction of category related behaviour of consumers.

The study results will help promote GC category adoption and usage which can benefit the environment and consumer health.

The study contributes to literature and practice by assessing a comprehensive set of critical antecedents to GC adoption using a novel approach of F-AHP and an expert user panel. The study results offer insights to marketers that can be used to develop suitable strategies to convert non-GC users into GCs in India and similar markets, improving category penetration and benefitting marketers, retailers, users, and the environment.

The study aims to analyse the role of digitisation in accounting in enhancing the overall effectiveness of accounting functions. To achieve this, the study provides empirical evidence from the stakeholder’s perspective of digitisation of accounting, auditing, reporting and regulatory compliance procedures.

The study has applied a quantitative approach to identify the thoughts of auditors, accountants and academicians on the impact of digitalised accounting applications on accounting functions. The data was collected by administering an empirical study and a sample of 482 professionals from the accounting, auditing and academic sectors. To analyse and interpret data descriptive statistics, structured equation modelling and mediation analysis has been used.

The finding of the study signifies the relevance of digitalised accounting applications in accounting functions and reveals that there is a significant impact of digitalisation on accounting, auditing, reporting and regulatory compliance aspects of accounting functions. The outcome of the study explores that a digitalised accounting system reduces possible errors and improves the accuracy and transparency of the system.

The study highlighted the importance of developing new methods and techniques that can be used in practice. This indirectly advocates the inclusion of such concepts in accounting curricula to emphasise the need to understand the challenges and opportunities created by digitisation. Furthermore, the study will become a motivation to scholars who intend to explore different areas through which new technologies can be adopted to transform traditional accounting systems.

The contributions of the current study have implications that the adoption of digitised accounting enhances economic efficiency through a reduction in accounting costs, and enhanced accuracy that leads to the elimination of penalties and litigations for non-compliance with regulatory authorities. This indirectly impacts positively on the financial health of the business organisations and economies at large. This implication becomes greater evidential support to the organisations which are yet to plan the adoption and implementation of digital tools in their organisation for accounting functions.

Digitalisation is a relevant part of the accounting function to improve efficiency and accuracy. Since accounting and auditing practitioners struggle to control the accuracy and efficiency of transactions. Furthermore, the outcome of the study assists organisations in gaining real-time access to financial data, transforms workflows and empowers management to make timely informed sound decisions, optimise resource allocation, efficient regulatory compliance and so on.