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The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

The implementation of the digital economy has had a considerable influence on the manufacturing industry, and this paper aims to address the important issues of how to capture the opportunities presented by digital innovation and promote the transformation and upgrading of the manufacturing industry, as well as the improvement of quality and efficiency.

Using panel data from 30 Chinese provinces and cities between 2010 and 2021, this study establishes the panel vector autoregression (PVAR) model and uses impulse response function analysis to evaluate the influence of the digital economy on the high-quality transformation and upgrading of China's small home appliance industry across five dimensions under the digital economy.

The development of digital infrastructure has not demonstrated a noteworthy capacity for advancing the transformation and upgrading of the small home appliance industry. Furthermore, digital industrialization has exerted a minimal restraining influence on this process. Nevertheless, digital governance has consistently exhibited a substantial impact on facilitating the transformation and upgrading of the small home appliance industry. While both industrial digitization and digital innovation hold significant potential for promoting the transformation and upgrading of the small home appliance industry, their sustainability remains limited.

The organization should logically join independent innovation and open innovation, construct an industrial ecosystem for the profound convergence of the digital economy and compact household appliances, use digital-wise science and technology to empower the establishment of brand effects, strengthen the portrayal of the digital standard framework for the intelligent compact household appliance industry, advance the development of a public stage for computerized administrations in the compact household appliance industry and develop a strategy ecosystem for computerized assets in the compact household appliance industry.

This study offers systematic evidence of the relationship between the digital economy and the development of the small home appliance industry. The results of this research contribute to the literature on the impact of the digital economy on the manufacturing sector and provide a logical explanation for the transformation and upgrading of the small home appliance industry within the context of the digital economy.

Previous studies on social influence and virtual product adoption have mainly taken users’ purchase behavior as a dichotomous variable (i.e. purchasing or not). Given the prevalence of competing versions (basic vs upgraded) of a virtual product in online communities, this paper investigated the differences in the effect of social influence on users’ adoption of basic and upgraded choices of a virtual product. It also examined how the effect varies with users’ social status and user-level network density.

A natural experiment was conducted in an online game community. Two competing versions (basic vs upgraded) of a virtual product were provided for in-game purchase while a random set of users selected from 897,765 players received the notification of their friends’ adoption information. A competing-risk model was used to test the hypotheses.

Social influence exerts a stronger positive effect on users’ adoption of the upgraded virtual product than of the basic virtual product. Middle-status users have the greatest (least) susceptibility to social influence in adopting the upgraded (basic) virtual product than low- and high-status users. User’s network density enhances the effect of social influence on adoption of both virtual products, even more for the upgraded one.

This research contributes to the social influence and product adoption literature by disentangling the different effects of social influence on basic and upgraded versions of a virtual product. It also identifies the boundary conditions that social influence works for each version of the virtual product.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

By comparing regression models, this study aims to analyze the added home value of green sustainability features and green efficiency characteristics, rather than green certifications, in the city of Austin.

The adoption of home green energy efficiency upgrades has emerged as a new trend in the real estate industry, offering several benefits to builders and home buyers. These include tax reductions, health improvements and energy savings. Previous studies have shown that energy-certified single-family homes command a premium in the marketplace. However, the literature is limited in its analysis of the effects of green upgrades and certification on different types of single-family homes. To address this gap, this research collected data from 21,292 multiple listing services (MLS) closed home-selling listings in Austin, Texas, over a period of 35 months.

The analysis results showed that green efficiency features could generally increase single-family housing prices by 11.9%, whereas green sustainability upgrades can potentially bring a 11.7% higher selling price. Although green housing certification did not have significant effects on most housing groups, it did increase closing prices by 13.2% for single-family residences sold at the medium price range, which is higher than the impacts from simply listing the green features on MLS.

The study contributes to the body of knowledge by examining the market value of broadly defined energy efficiency and sustainability features in the residential housing market. The findings can help policymakers, brokerage firms, home builders and owners adjust their policies and strategies related to single-family home sales and mortgage approvals. The research also highlights the potential benefits of capitalizing on green housing features other than certifications.

This study aims to examine how the legitimacy of internal auditing is reconstructed during enterprise resource planning (ERP)-driven technological change.

The study is based on the comparative analysis of internal auditing and its transformation due to ERP implementations at two case firms operating in the food sector in Egypt – one a major Egyptian multinational corporation (MNC) and the other a major domestic company (DC).

Internal auditors (IAs) at MNC saw ERP implementation as an opportunity to reconstruct the legitimacy of internal auditing work by engaging and partnering with actors involved with the ERP change. In doing so, the IAs acquired system certifications and provided line functions and external auditors with data-driven business insights. The “practical coping mechanism” adopted by the IAs led to the acceptance (and legitimacy) of their work. In contrast, IAs at DC adopted a purposeful strategy of disengaging, blaming and rejecting since they were skeptical of the top management team's (TMT's) sincerity. The “disinterestedness” led to the loss of legitimacy in the eyes of the stakeholders.

The article offers two contributions. First, it extends the literature by highlighting a spectrum of behavior displayed by IAs (coping with impending issues vs strategic purposefulness) during ERP-driven technological change. Second, the article contributes to the literature on legitimacy by highlighting four intertwined micro-processes – participating, socializing, learning and role-forging – that contribute to reconstructing the legitimacy of internal auditing.

Energy consumption has increased significantly since the 1970s, which has increased demand for sufficient infrastructure in the oil and gas industry. Many top-notch oil and gas companies invested in and equipped their facilities with high-capacity electrical equipment to meet high demand and benefit from high revenues. This is becoming a challenge nowadays for old facilities in the oil and gas industry, as most of the electrical equipment installed has reached or even exceeded its lifetime. Moreover, many of the original equipment manufacturers (OEMs) for electrical equipment from the 1980s are no longer in market today. Therefore, the aim of this study is to develop a proactive, cost-effective obsolescence management framework for electrical equipment in the oil and gas industry, considering the aging factor of the equipment.

Firstly, the study begins with gathering available information and identifying criteria. Secondly, the data collection is evaluated by subject-matter-experts (SMEs) in asset management field to ensure compliance with updated international standards and relevant regulatory requirements. Thirdly, a multi-criteria decision-making process is used to rank criteria. Finally, a scoring system is developed to measure the electrical equipment obsoleteness.

The developed framework will assist decision-makers in making informed decisions about maintenance, replacement or upgrades, using knowledge from previous studies and experts’ input. The result finding indicates that considering aging correction factors when measuring equipment obsoleteness leads to accurately and correctly predicting the electrical equipment obsoleteness score.

Previous studies have addressed obsolescence management without taking equipment age into account, regardless of how the equipment is performing. Thus, the lack of a comprehensive obsolescence management framework that accounts for both cost-effectiveness and the aging factor in the oil and gas industry poses a critical challenge.

This paper evaluates the factors influencing the utilization of the Internet of Things (IoT) for sustainable facilities management (SFM) practices in Saudi Arabia.

A mixed approach, combining a literature review, pilot-testing and questionnaire survey, was adopted to evaluate the factors. Twenty-seven factors were identified and grouped into four groups: technical, business and organizational, operational and security and privacy. The questionnaire was distributed to 30 facilities managers and 30 IoT specialists, totaling 60 practitioners, to determine the effect index of each factor. The practitioners' consensus on the ranking of the factors was then determined.

The study identifies the top-ranking factors as: “Difficulty in ensuring data security and protection,” “Difficulty in ensuring data privacy and confidentiality” and “Limited awareness and understanding of IoT benefits and capabilities.” These factors highlight the challenges to successful IoT implementation in the FM sector. The FM sector could benefit from utilizing IoT while maintaining the security, privacy and effectiveness of building operations by successfully addressing these concerns. A high level of consensus on the ranking of the factors was observed between facilities managers and IoT specialists. This was substantiated by a Spearman’s rank correlation coefficient of 0.79.

This study enriches the literature by combining practical insights from facilities managers with technical expertise from IoT specialists on the factors impacting IoT implementation in the Saudi Arabian FM sector. Beyond academic contributions, it provides practical insights for industry professionals, fostering a culture of knowledge-sharing and guiding future research in this field.

Recently, the popularity of software has grown significantly in the market. Enhancement of software is needed to decrease the burden of getting high-quality and reliable software. To achieve this, the software is upgraded by adding new features to the previous version. Therefore, adding new features in the last version to be consistent with the earlier version is challenging. This paper aims to discuss the optimal software enhancement and customer growth model.

This paper discusses a model when new features are added to the software, and the customers' adoption of the software is presented as a customer growth model. An optimal control problem is introduced to maximize the profit obtained from the software system over the system's lifetime period. Total gain is calculated by the value generated from selling the software over the total expenditure during the software development process. The closed-form solution and some theoretical results are presented using the optimal control-theoretic approach. The theoretical results are supported by a numerical example.

This paper gives several substantive insights during sensitivity analysis and provides essential results. The results discussed here are compatible with the actual scenario and useful in software enhancement.

The authors have proposed a new feature growth and customer growth model to maximize the total profit using optimal control theory.

This paper aims to trial a novel method of improving the performance of rail systems. Accordingly, an evaluation of rail system dynamics (SD) using discrete event simulation (DES) will be undertaken. Globally, cities and their transportation systems face ongoing challenges with many of these resulting from complicated rail SD. To evaluate these challenges, this study utilized DES as the basis of the analysis of Melbourne Metro Rail's SD. The transportation SD processes including efficiency and reliability were also developed.

Using DES, this research examines and determines the Melbourne Metro Rail's SD. Although the Melbourne Metro Rail is still in progress, the DES developed in this research examined the system requirements of functionality, performance and integration. As the basis of this examination, the Melbourne Metro Rail's optimization was simulated using the developed DES. As the basis of the experiment, a total of 50 trials were simulated. This included 25 samples for each of efficiency and reliability. The simulation not only scrutinized the SD but also underlined some of its shortfalls.

This study found that information and communication technology (ICT) was the pinnacle of system application. The DES development highlighted that both efficiency and reliability rates are the essential SD and thus fundamental for Melbourne Metro Rail system functionality. Specifically, the three elements of SD, capacity, continuity and integration are considered critical in improving the system functionality of Melbourne Metro Rail.

This particular mega rail infrastructure system was carefully analyzed, and subsequently, the DES was developed. However, since the DES is at its inception, the results are relatively limited without inclusive system calibration or validation process. Nonetheless, with some modifications, such as using different KPIs to evaluate additional systems variables and setting appropriate parameters to test the system reliability measures at different intensities, the developed DES can be modified to examine and evaluate other rail systems. However, if a broader system analysis is required, the DES model subsequently needs to be modified to specific system parameters.

Through evaluation of Melbourne's Metro Rail in the manner described above, this research has shown the developed DES is a useful platform to understand and evaluate system efficiency and reliability. Such an evaluation is considered important when implementing new transport systems, particularly when they are being integrated into existing networks.

Efficient rail networks are critical for modern cities and such systems, while inherently complex, aid local economies and societal cohesion through predictable and reliable movement of people. Through improved system functionality and greater efficiencies, plus improved passenger safety, security and comfort, the traveling public will benefit from the enhanced reliability of the transportation network that results from research as that provided in this paper.

This research paper is the first of its kind specifically focusing on the application of DES on the Melbourne Metro Rail System. The developed model aligns with the efficiency optimization framework, which is central to rail systems. The model shows the relationship between increased efficiency and optimizing system reliability. In comparison with more advanced mathematical modeling, the DES presented in this research provides robust, but yet rapid and uncomplicated system enhancements. These findings can better prepare rail professionals to adequately plan and devise appropriate system measures.