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The authors study how cloud adoption decision making unfolds in organizations and present the dynamic process leading to a decision to adopt or reject cloud computing. The authors thus complement earlier literature on factors that influence cloud adoption.

The authors adopt an interpretive epistemology to understand the process of cloud adoption decision making. Following an empirical investigation drawing on interviews with senior managers who led the cloud adoption decision making in organizations from across Europe. The authors outline a framework that shows how cloud adoptions follow multiple cycles in three broad phases.

The study findings demonstrate that cloud adoption decision making is a recursive process of learning about cloud through three broad phases: building perception about cloud possibilities, contextualizing cloud possibilities in terms of current computing resources and exposing the cloud proposition to others involved in making the decision. Building on these findings, the authors construct a framework of this process which can inform practitioners in making decisions on cloud adoption.

This work contributes to authors understanding of how cloud adoption decisions unfold and provides a framework for cloud adoption decisions that has theoretical and practical value. The study further demonstrates the role of the decision-leader, typically the CIO, in this process and identifies how other internal and external stakeholders are involved. It sheds light on the relevance of the phases of the cloud adoption decision-making process to different cloud adoption factors identified in the extant literature.

The successful implementation of hospital projects (HPs) tends to confront sundry challenges in the planning and construction (P&C) phases due to their complexity and particularity. Employing key performance indicators (KPIs) facilitates the monitoring of HPs to advance their successful delivery. This study aims to comprehensively investigate the KPIs for hospital planning and construction (HPC).

The KPIs for HPC were identified through a systematic review. Then a comprehensive assessment of these KPIs was performed utilizing a meta-analysis method. In this process, basic statistical analysis, subgroup analysis, sensitive analysis and publication bias analysis were performed.

Results indicate that all 27 KPIs identified from the literature are significant for executing HPs in P&C phases. Also, some unconventional performance indicators are crucial for implementing HPs, such as “Project monitoring effectiveness” and “Industry innovation and synergy,” as their high significance is reflected in this study. Despite the fact that the findings of meta-analysis are more trustworthy than those of individual studies, a high heterogeneity still exists in the findings. It highlights the inherent uncertainty in the construction industry. Hence, this study applied subgroup analysis to explore the underlying factors causing the high level of heterogeneity and used sensitive analysis to assess the robustness of the findings.

There is no consensus among the prior studies on KPIs for HPC specifically and their degree of significance. Additionally, few reviews in this field have focused on the reliability of the results. This study comprehensively assesses the KPIs for HPC and explores the variability and robustness of the results, which provides a multi-dimensional perspective for practitioners and the research community to investigate the performance of HPs during the P&C stages.

This study aims to investigate why and how shared service centres (SSCs) are implemented as well as how they affect audit firm practice and audit quality.

In this qualitative study guided by the theoretical framework of institutional theory, the authors conducted 25 semi-structured interviews in seven European countries, including 16 interviews with audit partners from Big 4 firms, 6 with audit team members, 2 with interviewees from second-tier audit firms and 1 with a member of an oversight body.

The authors show that the central rationale for audit firms to implement SSCs is economic rather than external legitimacy. The authors find that SSC implementation has substantial effects on audit practices, particularly those related to standardisation, coordination and monitoring activities. The authors also highlight the potential impacts on audit quality.

By exploring the motivation for and effects of SSC implementation amongst audit firms, the authors offer insights into the best practices related to subsequent change processes and audit quality.

This paper examines the relationship between marketing automation emergence and the marketers' use of heuristics in their decision-making processes. Heuristics play a role for the integration of human decision-making models and automation in augmentation processes, particularly in marketing where automation is widespread.

This study analyzes qualitative data about the impact of marketing automation on the scope of heuristics in decision-making models, and it is based on evidence collected from interviews with twenty-two experienced marketers.

Marketers make extensive use of heuristics to manage their tasks. While the adoption of new automatic marketing tools modify the task environment and field of use of traditional decision-making models, the adoption of heuristics rules with a different scope is essential to defining inputs, interpreting/evaluating outputs and control the marketing automation system.

The paper makes a contribution to research on the relationship between marketing automation and decision-making models. In particular, it proposes the results of in-depth interviews with senior decision makers to assess the impact of marketing automation on the scope of heuristics as decision-making models adopted by marketers.

The purpose of this paper is to propose and validate a robust industrial control system. The aim is to design a Multivariable Proportional Integral controller that accommodates multiple responses while considering the process's control and noise parameters. In addition, this paper intended to develop a multidisciplinary approach by combining computational science, control engineering and statistical methodologies to ensure a resilient process with the best use of available resources.

Taguchi's robust design methodology and multi-response optimisation approaches are adopted to meet the research aims. Two-Input-Two-Output transfer function model of the distillation column system is investigated. In designing the control system, the Steady State Gain Matrix and process factors such as time constant (t) and time delay (?) are also used. The unique methodology is implemented and validated using the pilot plant's distillation column. To determine the robustness of the proposed control system, a simulation study, statistical analysis and real-time experimentation are conducted. In addition, the outcomes are compared to different control algorithms.

Research indicates that integral control parameters (K_i) affect outputs substantially more than proportional control parameters (K_p). The results of this paper show that control and noise parameters must be considered to make the control system robust. In addition, Taguchi's approach, in conjunction with multi-response optimisation, ensures robust controller design with optimal use of resources. Eventually, this research shows that the best outcomes for all the performance indices are achieved when Kp11 = 1.6859, Kp12 = −2.061, Kp21 = 3.1846, Kp22 = −1.2176, Ki11 = 1.0628, Ki12 = −1.2989, Ki21 = 2.454 and Ki22 = −0.7676.

This paper provides a step-by-step strategy for designing and validating a multi-response control system that accommodates controllable and uncontrollable parameters (noise parameters). The methodology can be used in any industrial Multi-Input-Multi-Output system to ensure process robustness. In addition, this paper proposes a multidisciplinary approach to industrial controller design that academics and industry can refine and improve.

The authors aim to analyze the inequality in accessing distance learning during COVID-19 school closures.

The authors use the Household Pulse Survey, which is an effort by the United States (US) government to measure the well-being of American families during the COVID-19 pandemic. The authors employ a regression analysis to estimate the inequality in accessing distance learning by race and household income.

Disadvantaged children from nonwhite and low-income families have much less access to distance learning, including less access to online classes, digital devices and the Internet. Schools are critical providers of the Internet and digital devices to children from disadvantaged households. Schools and parents devote more attention to these nonwhite children by spending extra time on their learning activities.

This paper estimates the inequality in accessing distance learning during the COVID-19 crisis. Also, the authors analyze the responses of schools and parents toward this inequality.

This paper examines the impact of fiscal constraints on education expenditure in Nigeria from 1981 to 2021, using annual time series data.

The study deployed cointegration techniques with structural breaks.

Cointegration was found between education expenditure, debt servicing (a proxy for fiscal constraint) and associated variables. In both the long and short run, debt servicing negatively and significantly impacts education expenditure. While government revenue has a positive and significant impact on education expenditure in the long and short run, political institution has a negative and significant impact in the long run. Political institution is thus critical to education financing in Nigeria. The impact of debt is positive and significant in the short run, but not significant in the long run. There is a unidirectional causality from debt servicing to education expenditure.

Political institutions are critical towards contracting only productive debts and checkmating the adverse political environment through political will that prioritizes education financing.

The study extends the empirical literature on the fiscal constraint-education expenditure first by investigating fiscal constraint-education expenditure nexus given the institutional environment, and second by extending the methodology using cointegration techniques in the midst of structural breaks.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2022-0682.

This study explores the role of rising US student loan debt in explaining income inequality.

The study uses the autoregressive distributed lag (ARDL) modeling approach to explore the short- and long-run impact of college debt on income inequality in the US through quarterly data over the period 2000–2019.

The results demonstrate the detrimental impact of student debt on national and regional income inequality. Moreover, the regional analysis highlights a more pronounced impact of student debt on income distribution in South and West regions. The findings document that these regions, with the lower student debt proportions, have the lowest average cost of attending college. Finally, the analysis explores two potential channels – i.e. race and homeownership – that could explain the link between college student debt and income inequality.

The results can be helpful for policymakers and researchers to formulate practical approaches for assessing and addressing the rising national student debt and income inequality.

This is the first, to the best of the author's knowledge, study that explores the impact of US college debt on income inequality.

The purpose of this study is twofold. Firstly, the study has investigated the changing scenario of gender bias in households' education expenditure and the socioeconomic factors responsible for it. Secondly, the study has estimated the inequality in education expenditure for the male and female students and determined the significance of socioeconomic variables in gender discrimination.

To address the above-mentioned issues, this paper has used the unit-level data of NSSO 52nd, 64th, 71st and 75th rounds from 1995–1996 to 2017–2018. The log linear regression model is applied to estimate factor impending average education expenditure dynamics. The Oaxaca–Blinder Decomposition method has been employed to measure gender discrimination, and the Lorenz curve and Gini coefficient are used to assess inequality among girls experiencing prejudice.

The study has discovered an gender bias in education expenditure against females during the study period in India. Further, it has been found that gender discrimination against girl students is decreasing. Moreover, the factors such as age, religion, castes, MPCE (income quantile), type of institution, present enrolment and type of education are responsible for this gender differences.

This paper uses 20 years of household-level data for study and suggests that discriminatory behaviour of households and credit constraints of the underdeveloped countries prevent investment in girl's education. Therefore, the state must pay for education of girls by offering scholarships and free or heavily subsidized education. In addition to this, awareness programs for gender equality should also be implemented by the government, especially in rural areas.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2022-0537.

This study aims to explore the intelligibility of communication with stakeholders as a result of accrual accounting adoption. It focuses on changes in the use of visual forms and the readability of text that occurred immediately after the adoption of accrual accounting in performance reports of Italian public universities.

The authors collect the stakeholder section of performance reports published before and after accrual accounting adoption. Then, the authors use manual and computer-assisted textual analysis. Finally, the authors explore the data using principal component analysis and qualitative comparative analysis.

This study demonstrates that switching from cash to accrual accounting provokes immediate changes in communication patterns. It confirms the significant reduction of readability and increase in visual forms after accruals accounting adoption. The results indicate that smaller universities especially put effort into increasing intelligibility while implementing a more complex accounting system. This study also finds a relation between the change in readability and the change in visual forms that are complementary, with the exception of several very large universities.

The findings underline the possibility of neutralising the adverse effects of accounting reform associated with its complexity and difficulties in understanding by the use of visual forms and attention to the document’s readability.

This paper adds a new dimension to the study of public sector accounting from the external stakeholder perspective. It provides further insight into the link between accrual accounting adoption and readability, together with the use of visual forms by universities.