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A maturity model for Industry 4.0 (I4.0 MM) with influencing factors is designed to address maturity issues in adopting Industry 4.0. Standardisation in I4.0 supports manufacturing industry transformation, forming reference architecture models (RAMs). This paper aligns key factors and maturity levels in I4.0 MMs with reputable I4.0 RAMs to enhance strategy for I4.0 transformation and implementation.

Three steps of alignment consist of the systematic literature review (SLR) method to study the current published high-quality I4.0 MMs, the taxonomy development of I4.0 influencing factors by adapting and implementing the categorisation of system theories and aligning I4.0 MMs with RAMs.

The study discovered that different I4.0 MMs lead to varied organisational interpretations. Challenges and insights arise when aligning I4.0 MMs with RAMs. Aligning MM levels with RAM stages is a crucial milestone in the journey toward I4.0 transformation. Evidence indicates that I4.0 MMs and RAMs often overlook the cultural domain.

Findings contribute to the literature on aligning capabilities with implementation strategies while employing I4.0 MMs and RAMs. We use five RAMs (RAMI4.0, NIST-SME, IMSA, IVRA and IIRA), and as a common limitation in SLR, there could be a subjective bias in reading and selecting literature.

To fully leverage the capabilities of RAMs as part of the I4.0 implementation strategy, companies should initiate the process by undertaking a thorough needs assessment using I4.0 MMs.

The novelty of this paper lies in being the first to examine the alignment of I4.0 MMs with established RAMs. It offers valuable insights for improving I4.0 implementation strategies, especially for companies using both MMs and RAMs in their transformation efforts.

Food systems research is typically focused on productivity and efficiency. But in the face of impending challenges of climate, investment, markets, and incomes small holders may do well to shift to diversity and sufficiency. The transition requires institutions such as Farmer Producer Organisations (FPOs) to play the role of intermediaries. This paper aims to understand this challenging phenomenon using a case from India.

In this article, drawing from the emerging literature of PO as a sustainability transition intermediary, this paper uses the case study of a women-owned FPO and explores its role in contributing to sustainable food systems through practices of non-pesticide management of agriculture. This paper explores, through non-participant observer methods, focus group discussions and interviews with multiple stakeholders how an FPO embeds sustainability in its purpose and the challenges faced in transforming producer and consumers towards sustainable food systems.

The study argues for early articulation of the “sustainability transition intermediary” role in the FPO’s vision and mission. Second, FPOs’ role of being a transition intermediary is impacted by the key stakeholders and the durability of relationship with them.

By studying FPOs in India, from the framework of sustainability transitions, this article adds to the limited literature that looks as POs as sustainability transition intermediaries.

This study aims to enhance understanding of malnutrition's effect on academic achievement of primary school students.

This is a descriptive, cross-sectional design built on Roy's adaptation model (RAM). This study uses a random cluster sample, consisting of 453 primary school students. Contextual stimuli (mother's educational level, income and child’s breakfast eating) and focal stimuli (wasting, thinness, body mass index and stunting) were examined regarding adaptive responses to student’s academic achievement.

The investigation revealed that Model 1, which took into account factors of age, gender, the frequency of breakfast, income, the number of family members and the education of mothers, explained 12% (R² = 0.12) of the variance in academic achievement. Stuntedness (β = −3.2 and p < 0.01), BMI (β = 0.94 and p < 0.001), family income per month (β = 5.60 and p < 0.001) and mother's education (β = 2.79 and p < 0.001) were the significant predictors in Model 2.

This study provides evidence that malnutrition is associated with ineffective academic achievement. Moreover, variables such as the mother's level of education, family income and the child’s breakfast consumption have a significant impact on academic achievements.

RAM is a useful framework for determining factors affecting people's reactions to difficult circumstances.

After completion of the case study, the students will be able to analyze the role of industry in strategic decision-making, examine the information and make judgments with the use of different models such as political, economic, social, technological, environmental & legal (PESTEL) and Porter’s five forces and formulate a marketing strategy for the future move of Diwan & Co. using the Company, Competitors, and Customers (3Cs) model.

This case study is about young entrepreneur Mr Mansha Ram, who was working in the battery industry and was contemplating launching a new product. A gap was found after extensive research. The research showed that there is a gap between sustainable, reliable and cost-efficient batteries in the market that must be filled. To discuss this opportunity, a meeting was called where all managers talked about their concerns, considering the cost constraint as well as shifts in Pakistani battery industry trends. Ram was a key person who had to decide whether to launch the product or not. Should he go for a new initiative and launch lithium-ion batteries or capitalized on existing technology, which was lead acid batteries? Which path should he take considering all the macroenvironmental factors, electric vehicles or renewable energy?

This case study can be taught in the final year of undergraduate classes and the first year of MBA classes. This case study is particularly designed for students to understand how a company makes decisions while keeping in view the macro- and microbusiness environment. Even if some businesses do not have cost constraints, these businesses still face the impact of other factors on their businesses, for that purpose, the case study will provide insights into why a comprehensive industry analysis is important. Furthermore, this case study keeps in view the competitiveness of the market and its impact on the decision-making of companies.

Teaching notes are available for educators only.

CSS 8: Marketing.

Cloud computing services gained huge attention in recent years and many organizations started moving their business data traditional server to the cloud storage providers. However, increased data storage introduces challenges like inefficient usage of resources in the cloud storage, in order to meet the demands of users and maintain the service level agreement with the clients, the cloud server has to allocate the physical machine to the virtual machines as requested, but the random resource allocations procedures lead to inefficient utilization of resources.

This thesis focuses on resource allocation for reasonable utilization of resources. The overall framework comprises of cloudlets, broker, cloud information system, virtual machines, virtual machine manager, and data center. Existing first fit and best fit algorithms consider the minimization of the number of bins but do not consider leftover bins.

The proposed algorithm effectively utilizes the resources compared to first, best and worst fit algorithms. The effect of this utilization efficiency can be seen in metrics where central processing unit (CPU), bandwidth (BW), random access memory (RAM) and power consumption outperformed very well than other algorithms by saving 15 kHz of CPU, 92.6kbps of BW, 6GB of RAM and saved 3kW of power compared to first and best fit algorithms.

The proposed multi-objective bin packing algorithm is better for packing VMs on physical servers in order to better utilize different parameters such as memory availability, CPU speed, power and bandwidth availability in the physical machine.

ChatGPT is an advanced artificial intelligence (AI) form that can generate human-like text based on large amounts of data. This paper aims to empirically examine the ChatGPT adoption level among Indian individuals by considering the key factors in determining individuals’ attitudes and intentions toward newly emerged AI tools.

This paper used “partial least square structural equation modeling” (PLS-SEM) to investigate the relation among several latent factors by applying a representative sample of 351 individuals.

This study found that trialability, performance expectancy and personal innovativeness significantly influence individuals' attitudes, while compatibility and effort expectancy do not significantly impact attitudes. Additionally, trialability, performance expectancy, effort expectancy, personal innovativeness and attitude significantly influence behavioral intentions. However, compatibility has an insignificant impact on behavioral intention. Moreover, the research highlights that attitude and behavioral intention directly correlate with actual use. Specifically, the absence of compatibility makes people hesitate to use technology that does not meet their specific needs.

These unique findings provide valuable insights for technology service providers and government entities. They can use this information to shape their policies, deliver timely and relevant updates and enhance their strategies to boost the adoption of ChatGPT.

This paper is one of the pioneering attempts to exhibit the research stream to understand the individual acceptance of ChatGPT in an emerging country. Moreover, it gained significant attention from individuals for delivering a unique experience and promising solutions.

A quick search of the headlines of major newspapers reveals a treasure trove of technology procurement gone wrong. While the private sector seems to adopt and implement new technology seamlessly and quickly to deliver for customers, the government struggles to accomplish technology purchases and integrations with the same ease. As governments in the United States are looking to retain their current workforce and attract the next generation of workers, the technological capabilities and ethos of governments will be paramount. With nearly every industry being transformed by technology and Generation T being the first generation to have an ingrained “technology first” mindset, the ability of governments to attract these workers depends, in large part, on the ability to transform their government technology culture, policies, and practices.

In this chapter, the authors examine the administrative branch and observe two key components at the root of most technology failures: poor organizational structure in the bureaucracy and the lack of an empowered Chief Information/Technology Officer. Building upon case studies from Massachusetts and California, this chapter looks at the factors related to failure or success to understand the technology procurement culture. The chapter concludes by presenting four key “best practice” principles of public policy and administration that can be implemented by almost any governmental entity to improve their acquisition and implementation of technology.

This paper aims to investigate the impact of the revised Code of Corporate Governance 2017 (CCG-2017) clauses pertaining to board independence, mandatory inclusion of female directors, audit committee (AC) chair independence and directors’ expertise on earnings manipulation.

Using an unbalanced panel of 323 listed companies from 2015 to 2019, this study uses panel data regression models with a robust methodology called difference-in-differences to tackle the potential endogeneity.

This study’s findings show that, as compared to the pre-CCG-2017 period, board- and AC-related variables increased significantly in the post-CCG-2017 period. Furthermore, financial experts on the board and board independence have a negative effect on discretionary accruals (DAs), whereas female directors and DAs are positively related, as is real activity manipulation. The AC-related variables, such as AC independence, expertise in AC, and AC chair independence, are significantly different from the preperiod to the postperiod, whereas their relationship is not according to the hypotheses of the study. Moreover, these results are robust to additional analysis of the alternative proxies for female directorship and the endogeneity problem.

The findings of this study have implications for regulators and practitioners who are concerned with the functions of the board of directors (BOD). The findings of this research study show that earnings management (EM) may be reduced by independent and expert directors. However, board gender diversity is not reducing the EM. Therefore, the decision to appoint female directors to the board should be based on their business and professional attributes rather than simply filling quotas or blindly adhering to regulations. Moreover, the findings of this research may assist the regulator in encouraging listed firms to enhance board governance via independence, diversity and competency, which are useful for effective monitoring.

This study fills a gap in the literature by providing the first evidence of country-specific regulation (CCG-2017), concerning the BOD and AC-related clauses on EM in Pakistan, which is missing in the relevant literature general and in Pakistan in particular.

The present article aims to investigate the squeeze effects on hematite suspension-based curved annular plates with Rosensweig’s viscosity and Kozeny–Carman’s porous structure under the variable strong magnetic field and slip in the Shliomis model. The variable magnetic field is utilised to retain all magnetic elements within the model. The aforementioned mechanism would have the benefit of generating a maximal field at the system’s required active contact zone.

The Kozeny–Carman globular sphere model is used for porous facing. Rosensweig’s extension of Einstein’s viscosity is taken into consideration to enhance the fluid’s viscosity, and Beavers and Joseph’s slip boundary conditions are employed to assess the slip effect.

The pressure and lifting force under squeezing are computed through modification of the Reynolds equation with the addition of Kozeny–Carman’s model-based porosity, Rosensweig’s viscosity, slip and varying magnetic field. The obtained results for the lifting force are very encouraging and have been compared with Einstein’s viscosity-based model.

Researchers so far have carried out problems on lubrication of various sliders considering Einstein’s viscosity only, whereas in our problem, Rosensweig’s viscosity has been taken along with Kozeny–Carman’s porous structure model.

This paper investigates how gender, ethnicity, and network membership interact to influence how small and medium-sized enterprise (SME) owner-managers become aware of finance support programmes developed by government policy and/or support schemes advanced by the banking industry.

Drawing on expectation states theory (EST), we develop eight sets of hypotheses and employ the UK SME Finance Monitor data to test them using bivariate probit regression analysis.

In general, network membership increases awareness, but more so for government programmes. We also find no differences between female and male owner-managers when in networks. However, we identify in-network and out-network differences by ethnicity, with minority females seemingly better off than minority males.

Business networks are better for disseminating government programmes than industry-led programmes. For native White women, network membership can enhance policy awareness advantage further, whilst for minorities, networks significantly offset the big policy awareness deficits minorities inherently face. However, policy and practice need to address intersectional inequalities that remain in access to networks themselves, information access within networks, and the significant out-network deficits in awareness of support programmes afflicting minorities.

This study provides one of the first large-scale empirical examinations of intersectional mechanisms in awareness of government and industry-led enterprise programmes. Our novel and nuanced findings advance our understanding of the ways in which gender and ethnicity interact with network dynamics in entrepreneurship.