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Development of (1T-type) ferroelectric random access memory (FeRAM) has most actively progressed since 1995 and motivated by the physical limits and technological drawbacks of the flash memory. 1T-type FeRAM implements ferroelectric layer at the field effect transistor (FET) gate. During the course of the investigation, it was very difficult to form a thermodynamically stable ferroelectric-semiconductor interface at the FET gate, leading to the introduction of one insulating buffer layer between the ferroelectric and the silicon substrate to overcome this problem. In this study, Al₂O₃ a high-k buffer layer deposited by plasma enhanced atomic layer deposition (PEALD) is sandwiched between the ferroelectric layer and silicon substrate.

Ferroelectric/high-k gate stack were fabricated on the silicon substrate and pt electrode. Structural characteristics of the ferroelectric (PZT) and high-k (Al₂O₃) thin film deposited by RF sputtering and PEALD, respectively, were optimized and investigated for different process parameters. Metal/PZT/Metal, Metal/PZT/Silicon, Metal/PZT/Al₂O₃/Silicon structures were fabricated and electrically characterized to obtain the memory window, leakage current, hysteresis, PUND, endurance and breakdown characteristics.

XRD pattern shows the ferroelectric perovskite thin Pb[Zr_0.35Ti_0.65]O₃ film with (101) tetragonal orientation deposited by sputtering and PEALD Al₂O₃ with (312) orientation showing amorphous nature. Multiple angle analysis shows that the refractive index of PZT varies from 2.248 to 2.569, and PEALD Al₂O₃ varies from 1.6560 to 1.6957 with post-deposition annealing temperature. Increase in memory window from 2.3 to 8.4 V for the Metal-Ferroelectric-Silicon (MFS) and Metal-Ferroelectric-Insulator-Semiconductor (MFIS) structure has been observed at the annealing temperature of 500°C. MFIS structure with 10 nm buffer layer shows excellent endurance of 3 × 109 read-write cycles and the breakdown voltage of 33 V.

This paper shows the feature, principle and improvement in the electrical properties of the fabricated gate stack for 1T-type nonvolatile FeFET. The insulating buffer layer sandwiched between ferroelectric and silicon substrate acts as a barrier to ferroelectric–silicon interdiffusion improves the leakage current, memory window, endurance and breakdown voltage. This is perhaps the first time that the combination of sputtered PZT on the PEALD Al₂O₃ layer is being reported.

With the advancement of digital transformation, it is important for e-retailers to use artificial intelligence (AI) for customer engagement (CE), as CE enables e-retail brands to succeed. Essentially, AI e-marketing (AIeMktg) is the use of AI technological approaches in e-marketing by blending customer data, and Retail 4.0 is the digitisation of the physical shopping experience. Therefore, in the era of Retail 4.0, this study investigates the factors influencing the use of AIeMktg for transforming CE.

The primary data were collected from 305 e-retailer customers, and the analysis was performed using a quantitative methodology.

The results reveal that AIeMktg has tremendous applications in Retail 4.0 for CE. First, it enables marketers to swiftly and responsibly use data to anticipate and predict customer demands and to provide relevant personalised messages and offers with location-based e-marketing. Second, through a continuous feedback loop, AIeMktg improves offerings by analysing and incorporating insights from a 360-degree view of CE.

The main contribution of this study is to provide theoretical underpinnings of CE, AIeMktg, factors influencing the use of AIeMktg, and customer commitment in the era of Retail 4.0. Subsequently, it builds and validates structural relationships among such theoretical underpinning variables in transforming CE with AIeMktg, which is important for customers to expect a different type of shopping experience across digital channels.

The purpose of this research is to establish a conceptual model to understand the impact of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) on the transition of a Circular Economy (CE). Also, the paper explores the combined impact of TPM, I4.0 and CE on the sustainability performance (SP) of manufacturing firms.

The conceptual model is proposed using the dynamic capability view (DCV) and empirically validated by partial least squares-structural equation modelling (PLS-SEM) using 304 responses from Indian manufacturing firms.

The results suggest that I4.0 positively impacts TPM, CE and SP, also showing TPM's positive impact on CE and SP. In addition, CE has a positive influence on the SP of manufacturing firms. Furthermore, CE partially mediates the relationship between I4.0 and SP with TPM and SP. The study also identifies TPM, I4.0 and CE as a new bundle of dynamic capabilities to deliver SP in manufacturing firms.

The present research adds to the knowledge and literature on DCV by identifying the importance of CE in the settings of I4.0 and TPM, especially in the context of sustainability. Also, the current study offers a new set of dynamic capabilities and provides some significant future recommendations for researchers and practitioners.

The best possible way for brick-and-mortar retailers to maximise engagement with personalised shoppers is capitalising on intelligent insights. The retailer operates differently with diversified items and services, but influencing retail atmospheric on personalised shoppers, the perception remains the same across industries. Retail atmospherics stimuli such as design, smell and others create behavioural modifications. The purpose of this study is to explore the atmospheric effects on brick-and-mortar store performance and personalised shopper's behaviour using cognitive computing based in-store analytics in the context of emerging market.

The data are collected from 35 shoppers of a brick-and-mortar retailer through questionnaire survey and analysed using quantitative method.

The result of the analysis reveals month-on-month growth in footfall count (46%), conversation rate (21%), units per transaction (27%), average order value (23%), dwell time (11%), purchase intention (29%), emotional experience (40%) and a month-on-month decline in remorse (20%). The retailers need to focus on three control gates of shopper behaviour: entry, browsing and exit. Attention should be paid to the cognitive computing solution to judge the influence of retail atmospherics on store performance and behaviour of personalised shoppers. Retail atmospherics create the right experience for individual shoppers and forceful use of it has an adverse impact.

The paper focuses on strategic decisions of retailers, the tactical value of personalised shoppers and empirically identifies the retail atmospherics effect on brick-and-mortar store performance and personalised shopper behaviour.

Mismanagement of municipal solid waste (MSW) has led to resource depletion, ecosystem degradation and socio-economic risks, emphasizing the necessity to promote sustainable circular economy (SuCE) practices. This article identifies relevant enablers and unveils their interconnected roles in facilitating a municipal solid waste management (MSWM) system aligned with the principles of SuCE.

To identify pertinent enablers for MSWM systems based on SuCE principles, the study conducted a literature review and engaged experts from waste management sectors and academia to consolidate the final list of enablers. Following this, the study investigated the inter-relationships among these enablers using both Interpretive Structural Modeling (ISM) integrated and fuzzy Matrix Impact Cross-Reference Multiplication Applied to a Classification (fuzzy MICMAC) with MATLAB.

The study identified a comprehensive set of 23 enablers and categorized them into four control measures instrumental for the effective integration of SuCE principles in the context of the Indian MSWM system. Notably, the analysis highlighted that “authoritative pressure” and “policy transformation” are the highly influential enablers.

The study emphasizes actionable implications for stakeholders in the Indian MSWM sector. Policymakers and governmental bodies can enforce “authoritative pressure,” “policy transformation” and “budget allocation”. Meanwhile, managers can focus on “promotion of SuCE awareness”, “formalizing the informal workforce”, “infrastructure modernization”, “stakeholder engagement and alignment”, “segregation strategy”, “disruption preparedness”, and “local-based strategy”.

This study proposed a unique ISM diagraph and cluster of enablers to enhance the novelty of the study.

This study aims to examine current research on the relationship between Operational Excellence and Healthcare 4.0 (H4.0) for healthcare organizations.

The authors have performed a systematic literature review of 102 documents published between 2011 and 2022 from the Scopus database to identify the research trends on Operational Excellence and H4.0. Through a descriptive bibliometric analysis, this study has highlighted the year-wise trend in publication, top authors, prominent sources of publications, the country-wise spread of research activities and subject area analysis. Furthermore, through content analysis, this study has identified four clusters and proposed directions for future research of each identified cluster.

Results reflect overall growth in this area, with a few parts of the world being underrepresented in research related to Operational Excellence and H4.0. The content analysis focused on describing challenges pertaining to healthcare industries and the role of Operational Excellence tools and H4.0 technologies in dealing with various healthcare delivery aspects. The authors concluded their analysis by proposing a theoretical framework and providing theoretical and managerial implications of the study.

To the best of the authors’ knowledge, the paper is one of the first to analyze the existing literature on the healthcare sector at the interface of Operational Excellence and H4.0 technologies. The conceptual framework and cluster-wise future research prepositions are some of the unique offerings of the study.

The new ways to complete financial transactions have been developed by setting up mobile payment (m-payment) platforms and such platforms to access banking in the financial mainstream can transact as never before. But, does m-payment have veiled consequences? To seek an answer, the research was undertaken to explore the dark sides of m-payment for consumers by extending the theory of innovation resistance (IR) and by measuring non-adoption intention (NAI).

Three hundred individuals using popular online m-payment apps such as Paytm, PhonePe, Amazon Pay and Google Pay were surveyed for the primary data. IBM AMOS based structural equation modelling (SEM) was used to analyse the data.

Each m-payment transaction leaves a digital record, making some vulnerable consumers concerned about privacy threats. Lack of global standards prevents consumers from participating in the m-payment system properly until common interfaces are established based on up-to-date standards. Self-compassion (SC) characteristics such as anxiety, efficacy, fatigue, wait-and-see tendencies and the excessive choice of technology effect contribute to the non-adoption of m-payment.

This study proposes a threat model and empirically explores the dark sides of m-payment. In addition, it also unveils the moderator's role of SC in building the structural relationship between IR and NAI.

The integration of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) is an emerging model, and the global pressure of various stakeholders raises scepticism of any emerging model towards providing sustainability. Therefore, this research aims to identify and rank the potential significant drivers of an integrated model of I4.0 and TPM to guide manufacturing enterprises towards sustainability.

This research follows a four-phase methodology including literature review and expert opinion to select the sustainability indicators and I4.0-integrated TPM key drivers, followed by employing the analytic hierarchy process approach for weight determination of sustainability indicators. The research then deploys the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prioritise the I4.0-integrated TPM key drivers based on their effect on various sustainability indicators. Finally, a sensitivity analysis is conducted to check the robustness of the TOPSIS.

The findings establish the top five most influential key drivers of an I4.0-integrated TPM system, which include top management support, formal I4.0 adoption program, mid-management involvement and support, solid TPM baseline knowledge and high engagement of the production team. These top drives can lead manufacturing firms towards sustainability.

The digitalisation of shop floor practices, such as TPM, could be adapted by shop floor managers and policymakers of manufacturing companies to deliver sustainability-oriented outcomes. In addition, this research may aid decision-makers in the manufacturing sector in identifying the most important drivers of I4.0 and TPM, which will assist them in more effectively implementing an integrated system of I4.0 and TPM to practice sustainability. The scope of TPM applicability is wide, and the current research is limited to manufacturing companies. Therefore, there is a huge scope for developing and testing the integrated system of I4.0 and TPM in other industrial settings, such as the textile, food and aerospace industries.

This research makes a first-of-its-kind effort to examine how an I4.0-integrated TPM model affects manufacturing companies' sustainability and how such effects might be maximised.

The development of innovation capability (IC) is a central issue for both practitioners and academicians. However, studies that investigate the dimension of IC in the context of micro-enterprises are absent. Based on capability-based view, the purpose of this paper is to identify important dimensions to build a scale to measure IC in micro-enterprises.

The study is based on focus group discussions for item generation and questionnaire survey on a sample of 379 micro-enterprises in India. The scale is developed with the help of exploratory factor analysis and confirmatory factor analysis. Statistical tests demonstrate that the scale presents composite reliability as well as discriminant and convergent validity.

The findings show that four dimensions form IC in micro-enterprises: resources, networking, risk taking and involvement.

This study develops a new scale, which is a measure of IC of micro-enterprises. The implications have been recommended, which focus upon entrepreneurs, academicians and policymakers interested in developing the IC of micro-enterprises in India.

This study aims to explain the Indian taxpayers’ harassment saga in the name of revenue collections by the taxmen.

The study gas adopted descriptive viewpoints supported by empirical evidence.

Pursuant to the recent amendments in the Act, a good number of Sections such as 132(1), 132(1 A) and 153 A have empowered the tax officials to conduct raids without explaining the reasons, call for papers for reopening assessments of cases of a decade old and has increased the quantum of penalty for the default period substantially.

The paper is an original one and free from plagiarism.