Search results

This study aims to propose a framework for Halal Food Sustainable Traceability, with the purpose of investigating the implementation of traceability and sustainability within organizations operating in the halal food industry as well as exploring the impact of these practices on organizational performance. This study examines the meat processing sector in Indonesia, focusing on medium to large-scale industrial operations. The rationale for this investigation stems from Indonesia’s substantial potential in the competitive worldwide halal food industry.

The research framework has been developed by an extensive review of relevant literature, with a specific emphasis on the cycle of the halal food sustainable traceability framework. This cycle encompasses four key stages, including the roles played by authorities, the process of standardization, the implementation phase and the importance of collaboration. The study analyses and validates data using partial least square-structural equation modeling and empirically tests the theoretical framework using 109 Indonesian halal food industry data.

The research identifies potential obstacles and difficulties that may arise during different phases of the halal food sustainable traceability framework. Concerns regarding authority, standardization, implementation and collaboration are among these. In addition, strategies for overcoming these obstacles are deliberated upon, including knowledge sharing, transparency, ongoing reporting and strategic collaboration.

The present study introduces a Halal Sustainable Traceability Framework that incorporates the principles of halal, traceability, sustainability and their effects on organizational performance. This study offers significant perspectives on the difficulties and resolutions pertaining to the traceability and sustainability of halal food in Indonesia.

The construction industry is frequently scrutinised by the public for a variety of issues, including waste, inefficiency, narrow profit margins, scheduling setbacks, budget overruns, quality concerns, trust deficits, transparency issues, coordination challenges, communication issues and fraud. The purpose of this paper is to assess the effect of blockchain technology adoption on the construction supply chain.

This study used a quantitative research approach through a questionnaire survey that was conducted among professionals in the Nigerian construction industry using the snowball sampling method, which resulted in a selection of 155 respondents. The collected data were analysed using partial least squares structural equation modelling, enabling a thorough assessment of the proposed relationships and offering valuable insights specific to the construction industry.

The study’s findings validated the conceptual framework established. The results indicated that implementing blockchain across all stages of the construction supply chain has the potential to improve the construction process. The study also revealed that blockchain technology will significantly affect the construction supply chain in a positive manner.

This research was carried out in the South-western region which is one of the six geo-political zones in Nigeria using a cross-sectional survey method. The study holds implications not only for local construction practices but will also contribute to the broader discourse on national construction sector challenges and possible solutions.

The findings of this study will be immensely beneficial to both professionals, practitioners and stakeholders in the Nigerian construction industry in learning about the potential of blockchain technology application in improving the construction supply chain.

The study in this paper constructed and evaluated a conceptual framework by exploring the connections between the variables. The results have significant implications for the construction sector, as they provide avenues for enhancing the construction process and the overall supply chain. These findings are valuable for researchers examining the potential effects of blockchain technology on the construction supply chain.

Living walls (LWs), vegetated walls with an integrated growth layer behind, are being increasingly incorporated in buildings. Examining plant characteristics’ comparative impacts on LWs’ energy efficiency-related thermal behavior was aimed, considering that studies on their relative effects are limited. LWs of varying leaf albedo, leaf transmittance and leaf area index (LAI) were studied for Antalya, Turkey for typical days of four seasons.

Dynamic simulations run by Envi-met were used to assess the plant characteristics’ influence on seasonal and orientation-based heat fluxes. After model calibration, a sensitivity analysis was conducted through 112 simulations. The minimum, mean and maximum values were investigated for each plant characteristic. Energy need (regardless of orientation), temperature and heat flux results were compared among different scenarios, including a building without LW, to evaluate energy efficiency and variables’ impacts.

LWs reduced annual energy consumption in Antalya, despite increasing energy needs in winter. South and west facades were particularly advantageous for energy efficiency. The impacts of leaf albedo and transmittance were more significant (44–46%) than LAI (10%) in determining LWs’ effectiveness. The changes in plant characteristics changed the energy needs up to ca 1%.

This study can potentially contribute to generating guiding principles for architects considering LW use in their designs in hot-humid climates.

The plant characteristics’ relative impacts on energy efficiency, which cannot be easily determined by experimental studies, were examined using parametric simulation results regarding three plant characteristics.

The escalating levels of greenhouse gas emissions have become a growing global concern, with household energy consumption emerging as a significant contributor. To develop effective public policies, it is crucial to understand the energy-saving behavior of households. This study delves into the determinants of energy-saving practices in a developing country.

The authors chose a multivariate probit model, as it allowed to look after possible correlations among seven energy-saving practices within households.

The findings underscore the significant influence of sociodemographic variables, such as gender, civil status, income and education, on energy-saving practices. Furthermore, the authors discovered that households where the head actively volunteers in social organizations are more likely to adopt energy-saving behaviors. Additionally, internet access positively contributes to pro-environmental behavior. This research reveals that certain energy-saving practices are interconnected, acting as complements or substitutes.

Recommendations for public policy include prioritizing education in rural areas to boost energy-saving practices, improving internet access in nonurban regions and promoting citizen involvement in social organizations to enhance environmental awareness and encourage energy-saving behavior. The authors contribute to literature evidencing that certain energy-saving practices are not independent of each other, they are rather complementary and, in some cases, substitutes.

Recommendations for public policy include prioritizing education in rural areas to boost energy-saving practices, improving Internet access in nonurban regions and promoting citizen involvement in social organizations to enhance environmental awareness and encourage energy-saving behavior.

Previous studies have overlooked these interdependencies, highlighting the necessity of a system of equations to yield more efficient estimates by considering correlations between error terms.

This study examines the importance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand. To this end, the authors construct a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model. The model encompasses several essential characteristics, including incomplete financial markets, incomplete exchange rate pass-through, deviations from the law of one price and a banking sector. The authors consider generalized Taylor rules, in which policymakers adjust policy rates in response to output, inflation, credit growth and exchange rate fluctuations. The marginal likelihoods are then employed to investigate whether the central bank responds to fluctuations in the exchange rate and credit growth.

This study constructs a small open economy DSGE model and then estimates the model using Bayesian methods.

The authors demonstrate that the monetary authority does target exchange rates, whereas there is no evidence in favor of incorporating credit growth into the policy rules. These findings survive various robustness checks. Furthermore, the authors demonstrate that domestic shocks contribute significantly to domestic business cycles. Although the terms of trade shock plays a minor role in business cycles, it explains the most significant proportion of exchange rate fluctuations, followed by the country risk premium shock.

This study is the first attempt at exploring the relevance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand.

This study aims to introduce a multilevel micro-foundational perspective on supply chain (SC) ambidexterity, grounded in organizational learning and adaptation research. It investigates the interplay of contextual factors, strategic orientation and a bundle of supply chain management practices to foster ambidextrous performance.

Leveraging a blend of perceptual and objective data and measures, this study explores the intricacies of macro and micro factors at multiple levels, offering empirical support for the research framework. The interrelationships among these factors are scrutinized through three analytical approaches: selection, interaction and system forms of interdependence analysis.

First, the authors offer empirical support for their conceptual model, illustrating that ambidexterity behavior and outcomes in the SC emanate from intricate interactions between macro and micro factors across various levels. Second, the authors present robust empirical evidence endorsing a system/gestalt form of interdependence analysis in capturing SC ambidexterity and performance. This analytical approach effectively captures the complementarity and contradictory interdependence among the opposing poles of efficiency and responsiveness.

The organizational and SC activity configuration faces numerous paradoxical tensions, such as profitability versus sustainability. This study offers valuable insights into establishing an ambidextrous system capable of navigating and addressing these paradoxical situations.

This paper aims to explore recent advances in drift compensation algorithms for Electronic Nose (E-nose) technology and addresses sensor drift challenges through offline, online and neural network-based strategies. It offers a comprehensive review and covers causes of drift, compensation methods and future directions. This synthesis provides insights for enhancing the reliability and effectiveness of E-nose systems in drift issues.

The article adopts a comprehensive approach and systematically explores the causes of sensor drift in E-nose systems and proposes various compensation strategies. It covers both offline and online compensation methods, as well as neural network-based approaches, and provides a holistic view of the available techniques.

The article provides a comprehensive overview of drift compensation algorithms for E-nose technology and consolidates recent research insights. It addresses challenges like sensor calibration and algorithm complexity, while discussing future directions. Readers gain an understanding of the current state-of-the-art and emerging trends in electronic olfaction.

This article presents a comprehensive review of the latest advancements in drift compensation algorithms for electronic nose technology and covers the causes of drift, offline drift compensation algorithms, online drift compensation algorithms and neural network drift compensation algorithms. The article also summarizes and discusses the current challenges and future directions of drift compensation algorithms in electronic nose systems.

The article investigates different types of strategies for managing user-generated content (UGC) and provides some insights into their implications.

A unique sample of Italian hotels with current and prospective customers in the digital environment is investigated. A taxonomy of user-provider interactions mediated by UGC is developed. A mixed approach was designed to meet the study aims. Firstly, an exploratory factor analysis was performed in order to illuminate different strategies of UGC and electronic word-of-mouth (E-WOM) management. Secondly, a cluster analysis was implemented in order to explain hoteliers' behavior toward users' contents.

The study results suggested the existence of three clusters, which reflected three different types of interactions between hotels and customers in the digital domain. Interestingly, most of Italian hotels were found to adopt a reductionist approach to UGC and E-WOM management, turning out to be ineffective to exploit them for the purpose of quality improvement and hospitality service excellence.

Hotels were found to be largely unaware of the importance of UGC and web-based communication with customers to improve their digital business strategy. Tailored management approaches are needed to realize the full potential of hotels' online content responsiveness for the purpose of value co-creation and service co-production.

This is one of the first studies investigating the strategic and management perspectives embraced by hotels to handle their interactions with customers in the digital arena.

This study aims to examine the interrelationships between social media marketing activities, self-brand connections, brand equity, trust and loyalty.

A total of 402 valid responses were collected from Amazon MTurk, and the data were subjected to partial least squares structural equation modeling and fuzzy-set qualitative comparative analysis (fsQCA).

Findings indicate that social media marketing activities strongly and positively influence self-brand connection, brand equity and brand trust. Moreover, brand loyalty was strongly and positively influenced by self-brand connection, brand equity and brand trust. Moreover, the findings from fsQCA indicate that three causal paths lead to a high level of brand loyalty, and one causal path determines a low level of brand loyalty.

This research extends current knowledge by bridging the literature between social media marketing activities and branding using self-brand connections. Additionally, this study uses the strength of two complimentary methods – symmetrical and asymmetrical modeling – to uncover how social media marketing activities bridge customer-brand relationships.

Este estudio examina las interrelaciones entre las actividades de marketing en redes sociales, las conexiones de marca propia, el valor de la marca, la confianza y la lealtad.

Se recopilaron 402 respuestas válidas de Amazon MTurk, y los datos fueron sometidos a PLS-SEM y análisis cualitativo comparativo con conjuntos difusos (fsQCA).

Los resultados indican que las actividades de marketing en redes sociales influyen fuertemente y de manera positiva en la conexión de marca propia, el valor de la marca y la confianza en la marca. Además, la lealtad a la marca es influenciada fuerte y positivamente por la conexión de marca propia, el valor de la marca y la confianza en la marca. Además, los resultados de fsQCA indican que tres vías causales conducen a un alto nivel de lealtad a la marca, y una determina un bajo nivel de lealtad a la marca.

Esta investigación amplía el conocimiento actual al vincular la literatura entre las actividades de marketing en redes sociales y el branding utilizando conexiones de marca propia. Además, este estudio utiliza dos métodos complementarios – modelado simétrico y asimétrico – para descubrir cómo las actividades de marketing en redes sociales construyen las relaciones entre cliente y marca.

本研究探讨社交媒体营销活动、自我品牌连接、品牌资产、信任和忠诚度之间的相互关系。

从亚马逊MTurk收集了402个有效回复, 并对数据进行了PLS-SEM和模糊集合质性比较分析 (fsQCA) 的处理。

研究发现, 社交媒体营销活动对自我品牌连接、品牌资产和品牌信任产生了强烈而积极的影响。此外, 自我品牌连接、品牌资产和品牌信任也对品牌忠诚度产生了强烈而积极的影响。fsQCA的结果显示, 导致高水平品牌忠诚度的有三条因果路径, 而导致低水平品牌忠诚度的有一条因果路径。

本研究通过构建社交媒体营销活动与品牌之间的桥梁, 利用自我品牌连接, 扩展了当前知识。此外, 利用对称和非对称建模两种互补方法的优势, 揭示了社交媒体营销活动如何建立客户品牌关系。