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Providing a comprehensive literature review to consolidate existing knowledge, advancements and future directions in the field. By synthesizing the state of research, this work enhances the understanding of Prescriptive Maintenance (PsM) methodologies, applications and potential benefits to assist researchers in identifying fruitful avenues for further investigation, and guide practitioners in implementing PsM strategies to improve maintenance outcomes in their industries.

Through a systematic, multistage, specialists audited analysis of peer-reviewed articles, conference papers, books sections, thesis, magazines and industry reports, this work provides a literature review analyzing PsM origins, definitions, enablers, outputs and emerging trends.

PsM concept evolved in recent years representing a shift from traditional maintenance, leveraging prescriptive analytics, data-driven modeling and optimization techniques to enable proactive decision-making and optimal resource allocation. By harnessing PsM, organizations can anticipate and mitigate failures, optimize maintenance actions and enhance asset reliability.

Existing literature points out the following challenges for PsM implementation: prescriptive analytics improvement, scalability of frameworks, development of prototypes, processes integration; PsM maturity assessment; asset health prognostics assertiveness, real-time data availability and adoption of cost functions to grasp business and environmental, social and governance (ESG) costs.

Optimal deployment of resources with little or no human intervention in the maintenance decision process and the creation of new services improving reliability and operational performance.

By optimizing maintenance, not only direct costs diminish but also environmental, social and governance (ESG) related costs decrease by reducing energy waste during equipment’s operating phase, assessing the ecological impact of providing maintenance to operators and line maintenance stakeholders and, consequently, minimizing or even eliminating harmful effects on the environment and the human.

Work consolidating existing PsM-related knowledge and indicating future work is a gap in the literature. This paper fills this gap.

It has been revealed that application of the differential form of Eringen’s nonlocal elasticity theory to some cases (e.g. cantilevers) leads to paradoxical results, and recourse must be made to the integral version of Eringen’s nonlocal model. The purpose of this paper, within the framework of integral form of Eringen’s nonlocal theory, is to study the bending behavior of nanoscale plates with various boundary conditions using the isogeometric analysis (IGA).

The shear deformation effect is taken into account according to the Mindlin plate theory, and the minimum total potential energy principle is utilized in order to derive the governing equations. The relations are obtained in the matrix-vector form which can be easily employed in IGA or finite element analysis. For the comparison purpose, the governing equations are also derived based on the differential nonlocal model and are then solved via IGA. Comparisons are made between the predictions of integral nonlocal model, differential nonlocal model and local (classical) model.

The bending analysis of nanoplates under some kinds of edge supports indicates that using the differential model leads to paradoxical results (decreasing the maximum deflection with increasing the nonlocal parameter), whereas the results of integral model are consistent.

A new nonlocal formulation is developed for the IGA of Mindlin nanoplates. The nonlocal effects are captured based on the integral model of nonlocal elasticity. The formulation is developed in matrix-vector form which can be readily used in finite element method. Comparisons are made between the results of differential and integral models for the bending problem. The proposed integral model is capable of resolving the paradox appeared in the results of differential model.

This paper aims to combine Eringen’s micromorphic and nonlocal theories and thus develop a comprehensive size-dependent beam model capable of capturing the effects of micro-rotational/stretch/shear degrees of freedom of material particles and nonlocality simultaneously.

To consider nonlocal influences, both integral (original) and differential versions of Eringen’s nonlocal theory are used. Accordingly, integral nonlocal-micromorphic and differential nonlocal-micromorphic beam models are formulated using matrix-vector relations, which are suitable for implementing in numerical approaches. A finite element (FE) formulation is also provided to solve the obtained equilibrium equations in the variational form. Timoshenko micro-/nano-beams with different boundary conditions are selected as the problem under study whose static bending is addressed.

It was shown that the paradox related to the clamped-free beam is resolved by the present integral nonlocal-micromorphic model. It was also indicated that the nonlocal effect captured by the integral model is more pronounced than that by its differential counterpart. Moreover, it was revealed that by the present approach, the softening and hardening effects, respectively, originated from the nonlocal and micromorphic theories can be considered simultaneously.

Developing a hybrid size-dependent Timoshenko beam model including micromorphic and nonlocal effects. Considering the nonlocal effect based on both Eringen’s integral and differential models proposing an FE approach to solve the bending problem, and resolving the paradox related to nanocantilever.

This article reviews the quantitative marketing literature on artificial intelligence (AI) through an economics lens. We apply the framework in Prediction Machines: The Simple Economics of Artificial Intelligence to systematically categorize 96 research papers on AI in marketing academia into five levels of impact, which are prediction, decision, tool, strategy, and society. For each paper, we further identify each individual component of a task, the research question, the AI model used, and the broad decision type. Overall, we find there are fewer marketing papers focusing on strategy and society, and accordingly, we discuss future research opportunities in those areas.

The authors explore the emergence of altmetrics and Open Access (OA) publishing and discuss why their adoption in the management field lags behind other fields such as life sciences. The authors draw on the status literature to discuss the knowledge production and consumption underpinned by the ‘Impact Factor’ metric and high-status ‘Toll Access’ journals and their implications. The authors explain the rise of altmetrics and OA publishing and their implications on the production and consumption of knowledge. The authors then examine the current situation, challenges and offer reflections on the management field’s progression towards a more open research regime in the digital era.

Following Hackett et al.'s treatment of the reasonably established role of leader‐member exchange (LMX) in employee outcomes, this paper seeks to examine the mechanism which operates between LMX and various work outcomes in an attempt to bridge this gap in the literature.

The hypotheses were tested using data from 306 working software professionals in India. Data were collected through a structured questionnaire that contained standardized scales of LMX (perceived contribution and affect), satisfaction, commitment, and citizenship behavior (loyalty).

A confirmatory factor analysis (CFA) was done to examine the dimensionality of the study variables. Results provide support to all the hypotheses.

Data were collected from a single source, direction of causality is assumed (not tested) and all the data were collected through self‐reports. Some measures are taken to control them.

The findings have implications for LMX enhancement interventions. Focusing on enhancement of the LMX‐Contribution dimension is more likely to improve the organization level commitment and citizenship behavior, whereas LMX‐Affect is likely to result in more affective reactions like satisfaction with the supervisor and the job.

The study adds to the literature by testing the proposed model in the Indian context, thus providing some empirical cross‐cultural validity to LMX‐subordinate‐related work outcomes relationships.

This paper aims to access the protective function of hybrid sol-gel coatings deposited on 304L stainless steel substrate in silane solutions containing a mixture of tetraethoxysilane, methyltriethoxysilane and glycidyloxypropyltrimethoxysilane with different pH values during various immersion periods.

The 304L stainless steels coated through 10 and 30 s of immersion in the silane solutions with pH values of 2.1 and 2.8 were exposed to NaCl solution. The corrosion resistance of the coated substrates was studied through taking advantage of electrochemical noise method as well as atomic force microscopy (AFM), water contact angle and field emission-type scanning electron microscopy (FESEM) surface analysis.

The electrochemical current noise, PSD (I) plot, noise resistance and characteristic charge as parameters extracted from electrochemical noise method indicated the superiority of eco-friendly silane coating deposited on the substrate surface during 10 s exposure to the solution, due to the film uniformity and homogeneity as confirmed by FESEM and AFM. Moreover, immersion of the stainless steel in the silane solution with pH 2.1, characterized by higher hydrolysis ratio, led to more effective corrosion control in the NaCl electrolyte according to the results of electrochemical noise and FTIR measurements.

The noise resistance and characteristic charge as electrochemical noise parameters were only used in this research to evaluate the protective behavior of the water-based silane sol-gel coatings. Future studies should examine the correlation between electrochemical noise data and the parameters extracted from other electrochemical methods, e.g. electrochemical impedance spectroscopy.

The data obtained in this research may provide an effective approach based on electrochemical noise method to screen the silane sol-gel coatings for protection of metallic substrates against corrosion.

According to the literature, no report can be found studying the effect of immersion time on a silane solution, including glycidyloxypropyltrimethoxysilane, tetraethoxysilane and methyltriethoxysilane, as well as the silane solution pH on the corrosion resistance of 304L stainless steel in NaCl solution through electrochemical noise method.

This chapter reviews the recent developments at the intersection of personalization and AI in marketing and related fields. We provide a formal definition of personalized policy and review the methodological approaches available for personalization. We discuss scalability, generalizability, and counterfactual validity issues and briefly touch upon advanced methods for online/interactive/dynamic settings. We then summarize the three evaluation approaches for static policies – the Direct method, the Inverse Propensity Score (IPS) estimator, and the Doubly Robust (DR) method. Next, we present a summary of the evaluation approaches for special cases such as continuous actions and dynamic settings. We then summarize the findings on the returns to personalization across various domains, including content recommendation, advertising, and promotions. Next, we discuss the work on the intersection between personalization and welfare. We focus on four of these welfare notions that have been studied in the literature: (1) search costs, (2) privacy, (3) fairness, and (4) polarization. We conclude with a discussion of the remaining challenges and some directions for future research.

Given the existing quality concerns of higher education (HE), particularly in the global South, the integration of Artificial Intelligence (AI) has been seen as a panacea to improve the quality of teaching learning in HE. AI Chatbots, like ChatGPT, have created profound resonance across HE systems with both positive and negative impacts. Within HE, expectations and concerns related to the quality of HE in general, and teaching learning in particular, loom. It is yet to be investigated how university teachers use AI chatbots in their teaching inside classrooms and its potential to enhance the quality of teaching learning in HE. This chapter sheds light on these questions based on in-depth qualitative interviews with faculty members from six universities in Pakistan. Using a thematic analysis approach, the findings highlight both positive and negative aspects of ChatGPT when used for teaching in HE. Based on the findings, we developed a four-stage framework highlighting faculty members' response to integrating ChatGPT for transforming teaching learning activities. We explain that transformation of teaching learning with AI requires educators to rethink teaching and learning – navigative response – and assess its integration – evaluative response. In conclusion, we discuss how the adoption of AI chatbots provides educators with authentic assessment but will certainly require skills to properly navigate. We further discuss the findings in literature around the quality of HE making some plausible predictions regarding whether chatbots can serve as a quality enhancement tool, mainly in the global South.

The purpose of this study is to improve the coating properties of shellac–epoxidised novolac blends by treatment with melamine formaldehyde resin (MF) at ambient temperature for its use as a coating material.

Epoxidised-novolac resin was synthesised by epoxidation of novolac resin with epichlorohydrin. Novolac resin was synthesised by reaction of phenol with formaldehyde in acidic medium. Shellac was blended with the epoxidised-novolac resin in solution in varying ratios and treated the blends with MF resin in fixed ratio. Coating properties of the treated compositions were studied using a standard procedure. The compositions were characterised with Fourier transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA) and scanning electron microscopic (SEM) spectroscopy.

Treatment of shellac–epoxidised-novolac blends with MF resin improved water and alkali resistance of the blends, besides enhancing gloss. Gloss in all the blends was uniformly increased on treatment with MF resin. Water resistance of the blends tremendously improved after treatment with MF resin. Contact angle of the blends against water increased while decreased against ethylene glycol and dioxane. The compositions were more resistant to polar solvent than non-polar ones, suggesting that the compositions shifted to hydrophobic (lipophilic) nature on treatment with the MF resin.

A specified concentration of MF resin was used in the study. Different concentrations of the MF resin can also be tried for treatment of shellac–epoxidised-novolac blends to see the effect of the resin on the blends.

Treatment of shellac–epoxidised-novolac blend with MF resin improved the coating properties of the blends. The formulation SeNB-64 is the best with high gloss, good impact, scratch hardness and water resistance, and hence can be used as coating material for metal surfaces.

Blending of shellac with epoxidised-novolac resin and treatment of the blends with the MF resin was done for the first time. The formulation SeNB-64 can be used as coating material for metal surfaces.