Industry Practitioners Research Articles

Understanding Climate Change by Modeling the Earth's Atmosphere as a Well‐Stirred Tank

AbstractComing to terms with climate change by understanding climate processes and their policy implications is essential not only for climate scientists and policymakers, but also for the general public, for industrial practitioners, and for engineers, including process system engineers. We have developed a simplified linear climate model (SLCM) to enable non‐specialists to explore the essential physical and chemical processes caused by greenhouse gas emissions. Trading‐off simplicity and accuracy, achieved by calibrating model parameters using established simple climate models, the SLCM allows (i) determining the climate impact of given past and future emissions, (ii) determining the amounts of CO2 removal needed to compensate for any unavoidable emissions of CH4 and N2O from agriculture, and (iii) back‐calculating emission pathways to meet specified global warming targets.

Enhancing Building Information Modeling Effectiveness Through Coopetition and the Industrial Internet of Things

The construction industry plays a crucial role in the global economy but faces significant challenges, including inefficiencies, high costs, and environmental impacts. Although Building Information Modeling (BIM) has been widely adopted as a solution to these issues, its practical impact remains limited. This study investigates how manufacturers can enhance their contributions to improve BIM’s effectiveness, proposing that coopetition practices—combining competition and cooperation—can positively influence these contributions, thereby enhancing the benefits of BIM. To explore this hypothesis, an Experimental Coopetition Network was implemented in the Portuguese ornamental stone (POS) sector, utilizing Industrial IoT technology to facilitate collaboration among selected companies. The study assessed the impact of coopetition practices on key performance indicators related to BIM, including on-time delivery, labor productivity, and CO2 emissions. The findings demonstrate significant improvements in scheduling, operational efficiency, and environmental sustainability, validating the hypothesis that coopetition practices can enhance manufacturers’ contributions to BIM. These results suggest that coopetition practices contribute to better project outcomes, increased competitiveness, and sustainability within the construction industry. Despite the promising results, the study acknowledges limitations such as the scope of the sample size and observation periods, indicating areas for future research. This research contributes to the theoretical framework of coopetition, aligning with the United Nations Sustainable Development Goals (SDGs), and provides valuable insights for industry practitioners and policymakers seeking to implement more sustainable construction practices.

Circular economy in developing countries for sustainable development: A review

A significant percentage of any nation’s economy comes from the building industry, and its performance can impact overall economic growth and development. This paper aims to identify the similarities and differences between the construction sector (CS) of developed and developing economies in terms of size, growth, and contribution to the Gross domestic product (GDP) to understand the similarities and variances in the CS dynamics, trends, and challenges, and to inform policy decisions and investments through the literature review. The study also explores the factors that affect the CS’s performance in both types of economies, such as government policies, market conditions, and technological advancements. This paper concludes that the CS in developed economies is more established and technologically advanced, but there is still significant room for growth in developing economies. Moreover, a framework is proposed that could assist developing nations in opting for the construction economy. Further, the review emphasizes the significance of government policies and investments in infrastructure development to stimulate the CS’s growth and support overall economic development. The results of the study will assist in enhancing understanding of the CS’s potential in both developed and developing economies and support decision-making for policymakers, industry practitioners, and academicians.

Systematic Review of Plant-Based Excipients in Topical Drug Delivery

AbstractThis review explores the use of plant-based excipients in topical drug delivery. The review examines the advantages and challenges of using plant-based excipients, as well as case studies that demonstrate their effectiveness in delivering drugs through the skin. The review also discusses future perspectives on the use of plant-based excipients, including the potential for developing new formulations and improving drug delivery efficiency. The findings of this review suggest that plant-based excipients have significant potential in topical drug delivery and could offer a more sustainable and natural alternative to synthetic excipients. Overall, this review provides valuable insights for researchers and practitioners in the pharmaceutical industry who are interested in developing new and innovative drug delivery systems.

EFFECT OF PUBLIC PRIVATE PARTNERSHIP FINANCING STRUCTURE ON COMPLETION OF GEOTHERMAL ENERGY DEVELOPMENT PROJECTS IN KENYA

Objective: To determine the effect of Public Private Partnership (PPP) financing structure on the completion of geothermal energy development projects in Kenya. Theoretical Framework: The study used agency and public choice theories to analyze the dynamics between PPP financing structure and completion of geothermal energy development projects. Methodology: A cross-sectional census survey in Kenya surveyed 48 geothermal energy development projects, collecting quantitative data through structured questionnaires and qualitative insights from industry regulators, financiers, and practitioners. A combination of descriptive, correlation, and linear regression statistical models were applied. Multiple diagnostics tests and data triangulation were performed. Results and Discussion: The study results provide strong statistical evidence depicting a positive relationship between PPP financing structure and the completion of geothermal energy development projects in Kenya. The findings suggest that as the level of PPP involvement increases, so does the likelihood of faster project completion. The study also reveals that a balanced PPP financing structure has a substantial effect on the completion of geothermal energy development projects. The analysis demonstrates that a hybrid PPP financing structure comprising recommended proportions of private and government equity, commercial and concessional loans, hybrid finance, and grants significantly affects project completion outcomes. Research Implications: The study emphasizes the significance of a structured PPP financing model, comprising private and government equity, concessional and commercial loans, hybrid finance, and mixed grants, in mitigating inherent PPP risks for enhanced project completion outcomes. In addition, effective government support measures and robust delivery capability of developers jointly influence the two variables in a significant manner. Originality/Value: This study uniquely analyzes the influence of PPP financing structure on the completion of geothermal energy development projects in Kenya, integrating quantitative and qualitative data for a comprehensive perspective, thus offering essential insights for stakeholders.

The Pervasive Impact of Software Engineering and Architecture: A Multi-Industry Analysis

This article presents a comprehensive analysis of the ubiquitous role of software engineering and architecture across diverse industries in the modern digital landscape. Through a combination of literature review, industry case studies, and expert interviews, we examine how core software engineering principles—such as scalability, security, user experience, and data management—are applied and adapted in sectors ranging from e-commerce and fintech to healthcare, transportation, media, manufacturing, and government services. Our findings reveal both common challenges and industry-specific innovations in areas such as blockchain technology, telemedicine, autonomous vehicles, and industrial IoT. We also explore emerging trends, including the integration of artificial intelligence, edge computing, and quantum computing, and their potential impact on future software architectures. Furthermore, this article addresses critical ethical considerations and societal implications, including data privacy, job displacement, and the digital divide. By synthesizing these multifaceted perspectives, we provide valuable insights for both industry practitioners and academic researchers, highlighting the transformative power of software engineering in shaping the technological foundations of contemporary society and identifying key areas for future research and development.

The benefits and costs of all-inclusive system from hoteliers’ point of view: a supply-side perspective

PurposeAll-inclusive (AI) packages and meal plans have been an essential component of leisure tourism and received a corresponding attention from the literature, particularly in the case of package tours. However, the existing body of research focuses on the motivations, attitudes and behaviors of tourists, thereby neglecting the supply-side perspective. Therefore, the purpose of this study is to explore the benefits and costs of AI systems from the perspective of hoteliers.Design/methodology/approachData were collected through 27 semi-structured interviews with lodging professionals through purposive sampling. This study adopted a qualitative research design and used thematic content analysis to explore the benefits and costs of AI system.FindingsThe thematic content analysis produced two main themes as facility-related factors and destination-related factors, which further classified as benefits and costs for the hotels and destinations.Originality/valueThis study extends current knowledge by providing a more comprehensive understanding of the benefits and costs of AI systems based on the hoteliers’ point of view, which reflects the supply-side perspective. The findings also offer valuable implications for industry practitioners and destinations to assess and manage the benefits and costs of the system.

From jobs to careers: drivers and barriers to career development in emerging labor markets

IntroductionThis study aims to reveal the intrinsic and extrinsic drivers of career development in emerging labor markets and to explore the impact of these drivers and barriers on career development. With the rapid transformation of global industrial structure, career development in emerging industries such as artificial intelligence, big data, new energy and e-commerce is gradually attracting attention.MethodsThis study utilizes a mixed research method of questionnaires and in-depth interviews. The research team distributed a total of 700 questionnaires to practitioners in China, the United States, Japan, Germany and India, and collected interview data from 20 industry practitioners. These data were analyzed from both quantitative and qualitative perspectives to analyze the drivers and barriers to career development, and structural equation modeling was used to analyze the relationship between career motivation, barriers, social networks, and career satisfaction.ResultsThe results indicate that career development motivation significantly and positively influences career satisfaction, while individuals with high career satisfaction perceive fewer career barriers. In addition, career barriers significantly influenced individuals’ perceptions of career discrimination. The study also found that social networks play an important supportive role in career development, and that extensive social networks increase career satisfaction. Individuals with high motivation were more resilient in the face of external barriers and were willing to retrain to improve their occupational skills.DiscussionTo promote career development in emerging industries, labor market policies should optimize and create fair and inclusive work environments for emerging industries. By eliminating gender, age, and racial discrimination and providing employee support programs, career development satisfaction and opportunities can be effectively enhanced.ConclusionRapid technological updates, high work pressure, and cross-cultural barriers in emerging industries are the main challenges to career development today. This study suggests that governments and enterprises should jointly provide flexible vocational training and support policies to help practitioners adapt to the rapidly changing occupational environment.

Resource Nexus for decision-making: an industry-community synergistic approach for textile wastewater management

ABSTRACT Although the textile industry is crucial to economic development, it is a significant polluter of global water sources through its wastewater discharge, which endangers aquatic ecosystems and neighboring communities. This study focuses on stakeholder perceptions from farming and fishing communities related to wastewater management in the Bangladesh textile industry. Using focus group discussions with stakeholders that focused on sustainability values and a Resource Nexus framing, the results emphasise the adverse effects of textile wastewater on neighbouring communities, spanning agriculture, livestock, and ecological resources. The findings also underscore a significant need for collaboration between the textile industry and neighbouring communities, emphasising the ongoing obligation of governance resources, such as monitoring, regulations, and proactive measures and advocates for engaging different stakeholders in the formulation of robust policies, stringent regulations, and concerted efforts across industry, government, and communities to deliver improved governmental monitoring, enforcement of regulations and transparency in wastewater management practices in the textile industry of Bangladesh. The study suggests that a Water-Energy-Ecosystems-Food (WEEF) Resource Nexus approach can enhance decision-making, promoting sustainable energy infrastructure, encourage increased treated wastewater reuse, and facilitate effective management for environmental resilience and socio-ecological systems sustainability. This study contributes valuable insights elicited from a WEEF Resource Nexus approach, offering guidance for policymakers, industry practitioners, and researchers in the textile industry and beyond, aiding in the understanding of resilient industry-community ecosystems.

Pola Penerapan Residensi Unggulan Melalui Pendekatan In-kind dan Matchmaking dalam Pengembangan Media Pembelajaran Seni Lintas Disiplin bersama Industri Kreatif Program Studi Pendidikan Seni Rupa

The implementation pattern of flagship residencies through in-kind and matchmaking approaches in developing interdisciplinary art learning media with the creative industry at the Fine Arts Education Study Program aims to enhance the quality and relevance of art education. This program integrates in-kind contributions from the creative industry with a matchmaking process to create productive collaborations between students and industry practitioners. Methods include residency selection, interdisciplinary art project development, and evaluation of program outcomes and impacts. The results show an increase in students' practical skills and interdisciplinary understanding, as well as the enrichment of the fine arts education curriculum through direct input from the creative industry. The implementation of this pattern is expected to strengthen the synergy between education and industry, and produce innovative and applicable art learning media

Linear and nonlinear causality in financial markets.

Identifying and quantifying co-dependence between financial instruments is a key challenge for researchers and practitioners in the financial industry. Linear measures such as the Pearson correlation are still widely used today, although their limited explanatory power is well known. In this paper, we present a much more general framework for assessing co-dependencies by identifying linear and nonlinear causalities in the complex system of financial markets. To do so, we use two different causal inference methods, transfer entropy and convergent cross-mapping, and employ Fourier transform surrogates to separate their linear and nonlinear contributions. We find that stock indices in Germany and the U.S. exhibit a significant degree of nonlinear causality and that correlation, while a very good proxy for linear causality, disregards nonlinear effects and hence underestimates causality itself. The presented framework enables the measurement of nonlinear causality, the correlation-causality fallacy, and motivates how causality can be used for inferring market signals, pair trading, and risk management of portfolios. Our results suggest that linear and nonlinear causality can be used as early warning indicators of abnormal market behavior, allowing for better trading strategies and risk management.

Proximal Policy Optimization with Population-based Variable Neighborhood Search Algorithm for Coordinating Photo-Etching and Acid-Etching Processes in Sustainable Storage Chip Manufacturing

In the complex process of manufacturing storage chips, the photo-etching and acid-etching stages play a crucial role, significantly affecting energy consumption and environmental impact. This paper introduces a novel Bi-Level Programming Model for Storage Chip Manufacturing (BLPM-SCM) aimed at optimizing the coordination between these two stages. The upper-level model focuses on minimizing the time it takes to complete wafer production, while the lower-level model seeks to reduce the number of acid-etching tanks used, thereby balancing production efficiency with resource utilization. To address the inherent complexity of the bi-level model, we present a hybrid meta-heuristic algorithm that combines Proximal Policy Optimization (PPO) with a Population-based Variable Neighborhood Search (PVNS) method. The PPO-PVNS algorithm enhances the intensification phase by adaptively selecting shaking and local search strategies, while PVNS supports the diversification phase, ensuring comprehensive exploration of the search space through iterative updates of the solution population. Extensive numerical experiments demonstrate the algorithm's superior performance and generalization capabilities in optimizing the manufacturing process. It significantly improves the coordination between the photo-etching and acid-etching stages, achieving dual optimization of energy consumption and environmental benefits. Furthermore, this study provides valuable insights and decision-making tools for industry practitioners, offering innovative solutions for scheduling optimization in the semiconductor sector and promoting more sustainable and efficient production practices.

Luxury fashion brands in metaverse retailing – a review of literature and practice

Purpose The purposes of this study are to identify the ways that luxury fashion brands can leverage in metaverse retailing, and give insights to practitioners in the fashion industry who are planning to launch metaverse retailing. Design/methodology/approach To offer a balanced view of available evidence, this study adopted a literature review approach and attempted to collect all existing academic journal articles on the issues related to metaverse retailing and luxury fashion brands. A comprehensive literature search was conducted in electronic databases Google Scholar, Web of Science, Scopus, Pro Quest and Science Direct from January 2023 to April 2024. Based on the results of the research in literature, real-life examples of luxury fashion brands were used to explain the ways that luxury fashion brands in the metaverse retailing can be put into practice. Findings The findings have revealed that there are many ways that luxury fashion brands can leverage in the metaverse retailing. The fusion of metaverse-related technologies provides brands with a wide platform of choices that can create immersive, personalized marketing experiences for customers. Four roles of metaverse are identified: (1) enhance of immersive experience; (2) provide big data interface to smart decision-making; (3) form high-fidelity simulated space; and (4) maintenance economic system and making of identification. To further enhance the four roles of metaverse, four types of technologies and 15 components for metaverse can be adopted by luxury fashion brands. Research limitations/implications While this paper provides a literature review and real-life examples of luxury fashion brands in the metaverse retailing to explain the findings, further research is needed to evaluate the effectiveness of current efforts in the development of luxury fashion brands in the metaverse retailing through collecting both quantitative and qualitative data. Also, future studies may attempt to explore the challenges of investigating consumers in response to luxury fashion brands in the metaverse retailing. Practical implications The metaverse is turning imagination into reality through the integration of multiple technologies and is gaining momentum in tech. With technology leading the way, business leaders and brands must not only rethink retail but also bring immersive shopping experiences into the future. Metaverse has immense potential to transform the retail industry, thus the leading global and local firms must embrace innovation and new technologies, and prioritize “metaverse transformation” for their business. Based on the results of this study, some emerging practices pertaining to metaverse retailing are provided. Originality/value To the best of the authors’ knowledge, it would seem that this is the first work that conducts a literature review of the relevant academic journal articles addressed to the practitioners or managerial audiences in the area of luxury fashion industry who are concerned about the development of metaverse retailing. This paper identifies the ways that luxury fashion brands can leverage in the metaverse retailing and gives insights to practitioners in the luxury fashion industry who are planning to launch metaverse retailing.

Examining the Tourism Development in Bulacan Province, Philippines: Assessing Factors Shaping Tourism Growth

This research endeavors to assess the current state of tourism in Bulacan Province in the Philippines, examining the factors that influence its growth. It aims to provide valuable insights for local policymakers, stakeholders, and industry practitioners. Employing a quantitative approach, data is collected through surveys and statistical analyses to gain a comprehensive understanding of tourism dynamics in Bulacan. Key factors affecting tourism expansion, such as landscape, accessibility, and hospitality, are closely examined. Challenges faced by tourists, particularly in transportation and accommodation, are highlighted as significant factors influencing their experiences. Strategies to address these challenges are explored, offering practical recommendations to enhance the province’s tourism potential. The study’s findings contribute to the existing knowledge on destination management and regional tourism development. They offer guidance to policymakers, tourism planners, and industry stakeholders in devising effective strategies to leverage Bulacan’s unique attributes, promoting sustainable tourism growth and establishing the province as a prominent tourist destination.

Determinants Of Reputable Underwriters In Green Bond Offering

This research paper delves into the process by which industrial companies issuing green bonds can secure certification from reputable underwriters. By analyzing data from international green corporate bond offerings from the period between 2014 and 2022, the study aims to unravel the factors that influence underwriter selection decisions. Using a logit model to address the potential biases, the research reveals specific firm and bond characteristics that significantly impact the likelihood of collaborating with reputable underwriters. The findings indicate that reputable underwriters exhibit a preference for larger firms demonstrating strong financial performance, dealing with larger bond sizes, and possessing distinct bond features such as callability and involvement in private placements. Additionally, variables like maturity periods, involvement in finance vehicles, credit ratings, and syndicate size emerge as crucial factors in underwriter selection processes. These insights highlight the critical factors that issuers must thoroughly assess when selecting underwriters with strong reputations. The significance role of underwriter credibility, capabilities, and reliability in shaping the landscape of green bond underwriting is emphasized. This analysis holds relevance for both academic research and industry practitioners within the realm of sustainable finance.

The Effect of ERP System Utilization, Inventory Management, and Interdivisional Collaboration on Supply Chain Operational Efficiency in the Automotive Industry

This study examines the impact of ERP system utilization, inventory management practices, and interdivisional collaboration on supply chain operational efficiency in Indonesia’s automotive industry. Using a quantitative approach, data were collected from 120 respondents and analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS 3). The results indicate that ERP system utilization, inventory management, and interdivisional collaboration contribute to supply chain efficiency, with a combined effect explaining 67% of the variance in operational efficiency. Findings highlight ERP systems’ role in enhancing real-time data sharing, inventory management’s impact on stock optimization, and collaboration’s ability to streamline cross-functional processes. This study provides insights for industry practitioners seeking to optimize supply chain performance through technology adoption, robust inventory practices, and cohesive interdepartmental collaboration.

A three-phase framework for mapping barriers to blockchain adoption in sustainable supply chain

PurposeBlockchain technology is one of the major contributors to supply chain sustainability because of its inherent features. However, its adoption rate is relatively low due to reasons such as the diverse barriers impeding blockchain adoption. The purpose of this study is to identify blockchain adoption barriers in sustainable supply chain and uncovers their interrelationships.Design/methodology/approachA three-phase framework that combines machine learning (ML) classifiers, BORUTA feature selection algorithm, and Grey-DEMATEL method. From the literature review, 26 potential barriers were identified and evaluated through the performance of ML models with accuracy and f-score.FindingsThe findings reveal that feature selection algorithm detected 15 prominent barriers, and random forest (RF) classifier performed with the highest accuracy and f-score. Moreover, the performance of the RF increased by 2.38% accuracy and 2.19% f-score after removing irrelevant barriers, confirming the validity of feature selection algorithm. An RF classifier ranked the prominent barriers and according to ranking, financial constraints, immaturity, security, knowledge and expertise, and cultural differences resided at the top of the list. Furthermore, a Grey-DEMATEL method is employed to expose interrelationships between prominent barriers and to provide an overview of the cause-and-effect group.Practical implicationsThe outcome of this study can help industry practitioners develop new strategies and plans for blockchain adoption in sustainable supply chains.Originality/valueThe research on the adoption of blockchain technology in sustainable supply chains is still evolving. This study contributes to the ongoing debate by exploring how practitioners and decision-makers adopt blockchain technology, developing strategies and plans in the process.

Menu fatigue: Exploring an obscure concept with problem-centred expert interviews

The study aims to explore menu fatigue by defining its dimensions and the actors involved. It also aims to establish a model that reflects the paradigmatic nature of the concept. Given the paucity of literature to support the objectives, it was considered appropriate to conduct the study using a qualitative research approach. Accordingly, a grounded theory approach with problem-centred expert interviews was used to collect data, which is recommended for investigating issues that are not clearly defined and not well established, with the direct contribution of those who have sufficient knowledge of the concept being researched. First, the "what" and "who" questions were put to the only actor identified in the literature, the customer. In this way, the definition of menu fatigue was broadened and other actors to be studied were identified. Similar questions were asked of other actors such as administrative and owner/manager chefs, kitchen staff and service staff, who were also found to be affected. This cumulative approach made it possible to select 24 experts to contribute to the study. Participants were identified through purposive and theoretical sampling. The results of the two-stage coding showed that menu fatigue is not only about monotony, which is the only dimension associated with the concept in the literature, but also about excessiveness, appearance and extra effort. While previous literature accepted menu fatigue in industrial settings as an issue of customer boredom and perceived monotony, the current paper extended the concept to include newly explored dimensions and actors. Secondly, the highlighted dimensions and actors were linked to their occurrence and subsequent outcomes to be presented in a model of menu fatigue that provides a more comprehensive understanding of the issue. The paper concludes with implications for both academic and industrial practitioners.

Exploring Strategies to Market SMEs’ Activities: The Role of Personality Traits and Travel Motivations in Tourist Activities

Traditionally, professionals in the tourism sector have been encouraged to segment their market based on socio-demographic variables. However, the multifaceted nature of tourist activity calls for consideration of psychological factors to effectively shape marketing strategies. This study aims to provide insights for tourism industry practitioners by investigating the roles of tourists’ personalities and travel motivations in shaping their activities and their commitment to sustainability in Cumbria, home to UNESCO World Heritage Sites like the Lake District National Park and Hadrian’s Wall. Data were collected using quantitative methods to identify correlations between personality traits, travel motivations, and tourist activities. Additionally, a qualitative focus group with SME representatives from Cumbria provided insights into their understanding of the model. The findings provide significant insights into how the relationships between personality traits, travel motivations, and tourist activities can benefit tourism SMEs. By comprehending tourists’ behaviour, SMEs can tailor their offerings to appeal to the right audience, mitigating the adverse effects of overtourism, and therefore do more than allude to the concept of sustainability. Using these insights, SMEs could make informed decisions and create more effective marketing strategies, fostering sustainable practices that benefit both their customers and the long-term viability of their businesses and the destination.

A comprehensive review of treasury management practices and their impact on corporate sustainability in emerging economies: Strategic insights from the oil and gas sector

Treasury management practices are critical for ensuring financial stability and fostering corporate sustainability, particularly in the volatile oil and gas sector of emerging economies. This comprehensive review examines the relationship between treasury management practices and corporate sustainability, focusing on strategic insights that can be drawn from the oil and gas industry. The review highlights the importance of effective cash management, risk assessment, and liquidity optimization as key components of successful treasury operations. The study categorizes treasury management practices into several essential areas, including cash flow forecasting, working capital management, investment strategies, and risk management frameworks. Each category is analyzed concerning its contribution to corporate sustainability, emphasizing the need for a holistic approach that aligns financial objectives with environmental and social considerations. The findings indicate that robust treasury management practices can significantly enhance operational resilience, improve resource allocation, and support long-term sustainability initiatives. Furthermore, the review discusses the challenges faced by oil and gas companies in emerging economies, such as economic instability, regulatory uncertainty, and fluctuating commodity prices. These challenges necessitate the adoption of innovative treasury strategies that not only safeguard financial assets but also promote sustainable business practices. By integrating sustainability metrics into treasury decision-making, companies can better manage risks associated with environmental regulations and stakeholder expectations. Additionally, the role of technology in modernizing treasury management is examined, particularly in terms of digital tools and platforms that enhance data analysis and decision-making capabilities. The review underscores the potential for fintech solutions to streamline treasury operations and improve transparency, thereby contributing to enhanced corporate sustainability. In conclusion, this review provides strategic insights into the interplay between treasury management practices and corporate sustainability in the oil and gas sector of emerging economies. The insights presented herein are intended to guide industry practitioners in developing effective treasury strategies that foster sustainable growth while addressing the unique challenges of the emerging market context.