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1 – 10 of 929Goitom Abera Baisa, Joachim G. Schäfer and Abebe Ejigu Alemu
This study aims to synthesize and analyze research on the Supply Chain Management Practices (SCMPs)-performance nexus, examine current knowledge, identify emerging trends, and…
Abstract
Purpose
This study aims to synthesize and analyze research on the Supply Chain Management Practices (SCMPs)-performance nexus, examine current knowledge, identify emerging trends, and provide plausible suggestions for future research engagements in the manufacturing sector in the context of Developing and Emerging Economies (DEEs).
Design/methodology/approach
Following a systematic review approach, this study analyzed 20 peer-reviewed scientific journal articles published between 2007 and 2021. The study sample was systematically selected from the Web of Science (WoS) and Google Scholar databases, following strict evaluation and selection criteria.
Findings
Numerous dimensions of SCMPs have been considered in the extant literature; however, six have stood out as the most common. In addition, operational performance stood out as the most widely investigated measure in the SCM literature. Moreover, SCMPs have predominantly shown positive effects on performance outcomes. Methodological issues that future studies should consider are suggested.
Research limitations/implications
The sample size was not sufficiently large relative to the rule of thumb set in the literature because of the scarcity of studies in the manufacturing sector in the DEEs context. Despite these limitations, the results of this study provide crucial insights into knowledge and practice.
Originality/value
This review is the first of its kind to examine the SCMPs-performance nexus in the context of DEEs. Based on the findings of this study, future research directions are proposed.
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Brijesh Sivathanu and Rajasshrie Pillai
This study aims to investigate the effect of deepfake video advertisements on hotel booking intention by applying the media richness theory (MRT) and information manipulation…
Abstract
Purpose
This study aims to investigate the effect of deepfake video advertisements on hotel booking intention by applying the media richness theory (MRT) and information manipulation theory (IMT).
Design/methodology/approach
A quantitative survey was conducted using a structured questionnaire to understand the effect of deepfake hotel video advertisements on booking intention. A large cross-section of 1,240 tourists was surveyed and data were analyzed with partial least squares structural equation modeling (PLS-SEM).
Findings
The outcome of this research provides the factors affecting the booking intention due to deepfake hotel video advertisements. These factors are media richness (MR), information manipulation (IM) tactics, perceived value (PV) and perceived trust (PT). Cognitive load and perceived deception (DC) negatively influence the hotel booking intention.
Practical implications
The distinctive model that emerged is insightful for senior executives and managers in the hospitality sector to understand the influence of deepfake video advertisements. This research provides the factors of hotel booking intention due to deepfake video advertisements, which are helpful for designers, developers, marketing managers and other stakeholders in the hotel industry.
Originality/value
MR and IMT are integrated with variables such as PT and PV to explore the tourists' hotel booking intention after watching deepfake video advertisements. It is the first step toward deepfake video advertisements and hotel booking intentions for tourists. It provides an empirically tested and validated robust theoretical model to understand the effect of deepfake video advertisements on hotel booking intention.
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Ramin Rostamkhani and Thurasamy Ramayah
This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of…
Abstract
This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.
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Brijesh Sivathanu, Rajasshrie Pillai, Mahek Mahtta and Angappa Gunasekaran
This study aims to examine the tourists' visit intention by watching deepfake destination videos, using Information Manipulation and Media Richness Theory.
Abstract
Purpose
This study aims to examine the tourists' visit intention by watching deepfake destination videos, using Information Manipulation and Media Richness Theory.
Design/methodology/approach
This study conducted a primary survey utilizing a structured questionnaire. In total, 1,360 tourists were surveyed, and quantitative data analysis was done using PLS-SEM.
Findings
The results indicate that the factors that affect the tourists' visit intention after watching deepfake videos include information manipulation tactics, trust and media richness. This study also found that perceived deception and cognitive load do not influence the tourists' visit intention.
Originality/value
The originality/salience of this study lies in the fact that this is possibly among the first to combine the Media Richness Theory and Information Manipulation for understanding tourists' visit intention and post-viewing deepfake destination videos.
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Narinder Kumar, Bikram Jit Singh and Pravin Khope
Inventory models are quantitative ways of calculating low-cost operating systems. These models can be either deterministic or stochastic. A deterministic model hypothesizes…
Abstract
Purpose
Inventory models are quantitative ways of calculating low-cost operating systems. These models can be either deterministic or stochastic. A deterministic model hypothesizes variable quantities like demand and lead time, as certain. However, various types of research have revealed that the value of demand and lead time is still ambiguous and vary unanimously. The main purpose of this research piece is to reduce the uncertainties in such a dynamic environment of Industry 4.0.
Design/methodology/approach
The current study tackles the multiperiod single-item inventory lot-size problem with varying demands. The three lot sizing policies – Lot for Lot, Silver–Meal heuristic and Wagner–Whitin algorithm – are reviewed and analyzed. The suggested machine learning (ML)–based technique implies the criteria, when and which of these inventory models (with varying demands and safety stock) are best fit (or suitable) for economical production.
Findings
When demand surpasses a predicted value, variance in demand comes into the picture. So the current work considers these things and formulates the proper lot size, which can fix this dynamic situation. To deduce sufficient lot size, all three considered stochastic models are explored exclusively, as per respective protocols, and have been analyzed collectively through suitable regression analysis. Further, the ML-based Classification And Regression Tree (CART) algorithm is used strategically to predict which model would be economical (or have the least inventory cost) with continuously varying demand and other inventory attributes.
Originality/value
The ML-based CART algorithm has rarely been seen to provide logical assistance to inventory practitioners in making wise-decision, while selecting inventory control models in dynamic batch-type production systems.
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This study aims to reveal the perspectives of the management and senior accountants on the subject regarding the effects of climate change on the business world, within the…
Abstract
This study aims to reveal the perspectives of the management and senior accountants on the subject regarding the effects of climate change on the business world, within the framework of utilisation of tools like strategic cost management and strategic management. An electronic form was sent repeatedly to the e-mail addresses of public companies listed on the Borsa Istanbul (BIST), which were obtained from the Public Disclosure Platform (PDP), between June 2018 and June 2019. According to the data obtained from the survey of this study, it is not possible to comment that these tools are effectively utilised in Turkey. Besides, it is also early to say that top management is fully aware of the need to manage climate change. This study contributes to the literature by revealing the view of management accountants and finance experts in Turkey on climate change.
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Richa Chugh, Valerie J. Lindsay, Nicholas J. Ashill and Dave Crick
This study explores the influence of informal “psychological contracts” (PCs), (as opposed to formal contractual relationships) on exporter–distributor relationships.
Abstract
Purpose
This study explores the influence of informal “psychological contracts” (PCs), (as opposed to formal contractual relationships) on exporter–distributor relationships.
Design/methodology/approach
Data were obtained from a sample of 127 exporting small and medium-sized enterprises (SMEs) in New Zealand. The authors employed partial least squares structural equation modeling (PLS-SEM) for analyzing the measurement and structural models.
Findings
Psychological contract fulfillment (PCF) enhances affective commitment and calculative commitment. Moreover, affective and calculative commitments mediate the relationship between PCF and export venture performance (EVP). The authors also find that institutional distance (ID) weakens the relationship between PCF and both affective and calculative commitment. Additionally, ID moderates the strength of the mediating mechanism for affective commitment; thus, the authors present a moderated-mediation model.
Originality/value
To date, international relationship marketing (IRM) literature has focused on PC breach, and business-to-business (B2B) marketing literature has focused on the effects of PCs on affective/relational commitment. This study offers novel insights by demonstrating the positive indirect effect of PCF on EVP via the mediating variables – affective and calculative commitment. The authors' findings also present a conditioning role of ID on the micro-level relationships of PCs.
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