Search results

Most of the proposed decision aid methods provide the user only with a prescriptive approach (quantitative analysis) without any descriptive approach (qualitative analysis). It is therefore not possible to justify and recommend ways of improvement. The purpose of this paper is to introduce visualization techniques to complement prescriptive approaches.

Visual techniques have been developed for the FlowSort sorting method, namely the FS‐GAIA and stacked bar diagrams.

It is found that with visual techniques, fine details can be captured, e.g. detection of incomparability (with FS‐GAIA) and the composition of a score (with stacked bar diagrams).

In the future, it is expected that other multi‐criteria decision methods will be complemented by prescriptive approaches.

A real case study is introduced in order to illustrate the practicality of the visual techniques. In this paper, the innovation performances of small and medium enterprises from the French Lorraine region are assessed.

It is expected that the quality of the decisions taken are improved because of being better informed.

The paper, using a real case study, provides important new tools to enhance decision quality.

In a globalized environment, small and medium enterprises (SMEs) are facing formidable challenges. Not only do they have to keep up their profitability, but there is also a pressure from various stakeholders to add to their environmental and quality performance .The solution obviously lies in continuously adopting and improving upon lean-green practices in their operations. This work aims at identifying, classifying and building up a duly tested robust ranked-order model of such “enablers”, related to lean-green practices, that puts them (the enablers) in an order of being the most significant to being the least significant further to be accorded the same or similar weight in strategy formulation and implementation stage by Indian SMEs for enhancing their overall organizational performance.

The study identifies 20 enablers (12 lean and 08 green manufacturing enablers) through extensive literature review and experts' opinion survey and classifies them into three main categories. The ranking and significance of each of the main and subcategory enablers is evaluated according to its weight which is determined by the best-worst method (BWM) approach, one of the novel multi-criteria decision-making (MCDM) methods. Further, the results have been drawn after running accuracy check of the rankings (based upon optimal weights) and testing the robustness of the ranked-order model through sensitivity analysis.

The results of this study reveal that out of the three main category enablers, “operational performance enablers (E1)” and “quality performance enablers (E3)” are the most and the least significant enablers, while in the group of 20 subcategory enablers, “Kaizen (E17)” and “environment emission control (E28)” are the most and the least significant subcategory enablers, respectively.

The prioritization model or ranked-order model of the lean-green manufacturing enablers proposed through this study may serve as a standard model to managers to help them decide and allocate their efforts and resources accordingly in managing their operations. This will also help them adopt high-ranking lean-green manufacturing enablers in their firms and benchmark and standardize their existing practices accordingly, leading to greater competitive advantage.

The study identifies various green-lean manufacturing enablers in SMEs, classifies them into three main categories and ranks them using BWM approach. The findings of this study should be extremely relevant to managers, manufacturing engineers and practitioners in Indian SMEs from the perspective of developing deeper appreciation of these enablers as per their relative ranked importance to further formulating an effective and efficient strategy for their implementation resulting in optimal results.

Humanitarian supply chains (HSCs) by their very nature require urgent reaction to unforeseeable needs, making it difficult to properly plan for the support of actual demands. As such, integrating sustainability into traditional HSC practices continues to present a challenge to governments, nongovernmental organizations (NGOs) and other humanitarian-related agencies. This study focuses on identifying and categorizing the leading enablers to green humanitarian supply chains (GHSCs) and proposes a model for improving the responsiveness based upon a fuzzy total interpretive structural modelling approach.

Total interpretive structural modelling (TISM) uses group decision-making to identify contextual relationships among each pair of enablers and elucidates the nature of each underlying relationship. The fuzzy TISM shows the level of strength (very high influence, high influence, low influence and very low influence) of each enabler in relation to other enablers, which can help to inform management decision-making.

GHSC management requires strategic planning of inventory and logistics management. The importance of collaborative relationship building with HSC partners for developing capability and the effective use of available resources are keys to success. These improved relationships also help to promote postponement and similar speculation-based logistics strategies, as well as advanced purchasing and pre-positioning strategies. Finally, the speed and quality of response is found to be the top enabler in GHSC management.

One noted shortcoming of the chosen research method is its reliance on subjective expert judgement. However, collecting judgements is at the basis of many research methods, and the research team took utmost care throughout the research process to allay biases. Future empirical research can further examine the relationships suggested herein. Managers can use the model developed in this research to consider impactful ways to design and execute sustainable HSCs.

To the best of the authors' knowledge, this is a novel attempt to identify enablers to GHSC management. Secondly, the research team has used an advanced methodology (fuzzy TISM) to develop the contextual inter-relationships among the enablers which has not been used earlier in this direction before and thus advances the GHSC literature.

This study is a follow-up of inpatients diagnosed with severe depression/melancholia between 1956 and 1969. During this period, all inpatients at the Department of Psychiatry, University Hospital, Lund, were rated on a multidimensional diagnostic schedule on discharge. There were 471 patients born from 1920 onward. In the present follow-up, 2006 to 2010, 169 survivors could be traced. They were asked to participate in the study involving a telephone interview, in which a structured life chart was used. Of the patients contacted, 16 were ill or confused and 3 did not remember ever being depressed, leaving 150 who could participate. Seventy-five of these agreed to participate in the study. Long-term course of depression was evaluated by cluster analysis and compared to background variables, such as heredity for depression, perceived parental rearing behaviour, and treatment of index depressive episode. Using a cluster analysis the patients could be separated into six clusters describing the course: i) single or few episodes followed by long-lasting remission; ii) single or few episodes followed by long-lasting remission, although shorter; iii) single or few episodes followed by late recurrence; iv) single or few episodes, but more frequently ill, followed by late recurrence; v) several episodes followed by lasting remission; vi) chronic course of episodes. Remission or recurrence could therefore occur even after more than a decade. In summary, there was a short-term course with or without recurrence or a chronic course with or without late remission. Heredity for depression was significantly related to a chronic course with or without late remission.

The purpose of this paper is to provide an insight about factors affecting Big Data Analytics (BDA) utilization and adoption in Indian firms. Research studies have so far focused on BDA adoption in developed economies. This study examines the factors that influence BDA usage and adoption in the context of emerging economies.

This study proposed a theoretical model of factors influencing BDA utilization and adoption. Two independent research streams – first, the top managers’ perceived strategic value (PSV) in BDA and second, the factors that influence the adoption of BDA theoretically – have been integrated with the technology-organization-environment (TOE) framework. In the BDA context, there was a theoretical necessity to identify the driver and barriers of BDA from the TOE framework on PSV and adoption of BDA. A qualitative exploratory study using face-to-face semi-structured interviews was carried out to collect data from 22 different enterprises and service providers in India. India was selected as the context as it is one of the fastest growing large economies of the world with huge potential of BDA to improve the business landscape.

The results showed that the major reason behind BDA non-adoption is that the organizations did not realize the strategic value (SV) of BDA, and they were not ready to make the changes because of technological, organizational and environmental difficulties. The findings corroborate previous results about significant factors affecting IT adoption and implementation and provide new and interesting insights. The main factors identified as playing a significant role in organizations’ adoption of BDA were SV of BDA, complexity, compatibility, IT assets, top management support, organization data environment, perceived costs, external pressure and industry type.

The main limitation related to this study is the difficulty in generalizing the findings to a larger population of enterprises. To overcome this, a statistical survey has been planned to be conducted in the future.

The BDA adoption model in this study will have both managerial implications for practitioners in India, as well as those in other developing countries, and academic implications for researchers who are interested in BDA adoption in developing counties, in terms of formulating better strategies for BDA adoption. For managers, using the research model of this study could assist in increasing their understanding of why some organizations choose to adopt BDA, while similar ones facing similar conditions do not. Also, the understanding of the strategic utilization of BDA in different business processes may improve the adoption of BDA in organizations.

This paper contributes in exploring and enhancing the understanding of the factors affecting the utilization and adoption of BDA in organizations from an Indian perspective. This study is an attempt to develop and explore a BDA adoption model by the fusion of PSV and TOE framework. The effect of the three contexts of this framework (technological, organizational and environmental) on the strategic utilization of BDA has been studied for the first time.

The paper focuses on reviewing and theorizing the factors that affect the adoption of cloud computing in the education sector narrowing the focus to developing countries such as India.

Through an extensive literature survey, critical factors of cloud computing for education were identified. Further, the fuzzy DEMATEL approach was used to define their interrelationship and its cause and effect.

A total of 17 factors were identified for the study based on the literature survey and experts' input. These factors were classified as causes and effects and ranked and interrelated. “Required Learning Skills and Attitude,” “Lack of Infrastructure,” “Learners' Ability” and “Increased Investment” are found to be the most influential factors.

The resultant ranking factors can be used as a basis for managing the process of cloud adoption in several institutions. The study could guide academicians, policymakers and government authorities for the effective adoption of cloud computing in education.

The study investigates interdependency amongst the factors of cloud computing for education in context with developing economy. This is one of first study in higher education institutes of India.

A spreadsheet program like Lotus 1–2–3 is perfect for computing an interrelated matrix of numbers, such as a salary schedule. It provides planners with the flexibility to conduct “what if …” analyses. In addition, its “lookup” function allows the planner to enter an employee's range and step and extract the relevant salary.

Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable competitive advantage and cope with uncertainties as well as disruptions. Although a wide range of studies exists on supply chain agility (SCA) from the perspective of antecedents or consequences, there is little research on the investigation of enablers of SCA and their relations among them. Furthermore, the literature has investigated proactive and reactive enablers for enhancing SCA, but most studies have not sufficiently framed their analysis of both aspects synchronically. This paper aims to find out the interrelationships among the proactive and reactive enablers for enhancing SCA.

An extensive literature review has been conducted to identify SCA enablers and a Delphi study has been performed to elucidate SCA enablers in the manufacturing industry in Turkey. Interpretive structural modeling (ISM) has been used to identify the contextual relationship among the SCA enablers, and the model has been validated based on Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC) analysis.

On theoretical and practical levels, the proposed ISM model in this study can help organizations analyze and interpret interrelationships among enablers of SCA. For managers, it can provide better insights and understanding of the facilitators of SCA to enhance the effectiveness of the supply chain and cope with uncertainties and turbulence. According to results, enhancing “supply and demand side competency”, “delivery speed” and “strategic sourcing” are the most significant enablers of SCA.

The study extends the existing literature related to the enablers of SCA by modeling the proactive and reactive enablers of SCA based on the Al Humdan et al. (2020) classification. Arranging the enablers of SCA in a hierarchy and classifying the enablers into different levels with the help of the ISM-MICMAC approach is an exclusive effort to achieve successful management of the supply chain.

Key audit matters (KAM) and their impact on the auditor is a relatively understudied area. The purpose of this study is to analyse whether auditors perceive that the recent requirement for auditors of listed companies to report KAMs has enhanced the transparency of audit reports or not, what additional risks they now face, how the risk is being managed and its impact on the relationship with their clients.

The paper uses an interpretive approach for detailed interviews with some of South Africa’s leading audit experts to highlight their perspective of the impact of KAM on audit reporting and the audit environment.

The experts have various perceptions of what makes a matter “key”. These vary from materiality, to subjectivity and difficulty, as well as incorporating a time-based consideration. Concerns identified include a significant increase in cost and an increase in potential liability, triggering the need for thorough internal risk management policies. The audit experts conclude that KAM has ultimately failed to achieve its goal of greater transparency, with clients virtually ignoring KAM reports.

The research relies on a relatively small sample of subject experts and may not provide a complete account of the view of all audit professionals and KAM reports issued. It analyses the impact of KAM from the preparers’ perspective.

This study contributes to the research conducted in this topical area. Although there has been research on KAM focusing on pre-implementation consequences, there is virtually no formal academic research on the impact KAM has had on audit partners and firms in South Africa post implementation. It may also serve as a basis for the IAASB to consider going forward.

Food is a key element in tourism experiences. This study aims to investigate the interplay of sensory and non-sensory factors in food tourism experiences and models their influence on satisfaction and behavioural intentions.

The study focuses on the culinary experiences of 304 tourists dining at ethnic restaurants and uses causal relationship discovery modelling to analyse data.

Sensory factors are important in tourists’ culinary experiences with cleanliness, noise levels and room temperature at the top of the causal chain. Results also indicate the interplay between sensory and non-sensory factors to explain overall satisfaction, intention to return and intention to say positive things.

Using embodied cognition theory, the study offers novel insights into the role of senses in food tourism experiences at rural destinations.

美食是乡村旅游的主要吸引物之一。本研究的目的是调查游客在用餐体验中感官和非感官因素的相互作用, 以及这些因素如何影响游客的满意度和行为意愿。

本研究使用因果关系建模的方法来分析 304 名在某地方特色餐厅用餐的游客的问卷数据。

结果显示, 对于游客的用餐体验而言, 感官和非感官因素具备同等的重要性。此外, 结果发现, 游客感知到的噪音水平、适宜的室内温度及清洁度在与其他因素的相互作用中非常重要, 并能激发游客的满意度和重游意愿。

基于认知理论, 本研究为更好地理解感官因素和非感观因素在乡村旅游情境下的游客用餐体验中的作用提供了新的知识。

La comida es un elemento clave en las experiencias turísticas. Este estudio investiga la interacción de factores sensoriales y no sensoriales en las experiencias de turismo gastronómico y modela su influencia en la satisfacción y las intenciones de comportamiento.

El estudio se centra en las experiencias culinarias de 304 turistas que cenan en restaurantes étnicos y utiliza modelos de descubrimiento de relaciones causales para analizar los datos.

Los factores sensoriales son importantes en las experiencias culinarias de los turistas con la limpieza, los niveles de ruido y la temperatura ambiente en la parte superior de la cadena causal. Los resultados también indican la interacción entre factores sensoriales y no sensoriales para explicar la satisfacción general, la intención de regresar y la intención de decir cosas positivas.

Utilizando la teoría de la cognición incorporada, el estudio ofrece nuevos conocimientos sobre el papel de los sentidos en las experiencias de turismo gastronómico en destinos rurales.