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This paper aims to quantify the trend of variables used for building a theoretical model with the help of analysing bibliometrics data of inventory management (IM) and Total Quality Management (TQM) practices and their effects on firm performance.

Scopus' research database and the Web of Science (WoS) (including Elsevier, Emerald Group Publishing, Taylor and Francis, Wiley, IEEE, Informs and SAGE) were used to find relevant articles. The articles, review papers and conference proceedings were screened from 1993 to 2021. The articles were analysed to explain the different types of IM practices, TQM practices and their effect on the firm's performance. Thematic analysis was done using a bibliometric package of “R” (Biblioshiny) and VOSviewer to identify the key trends, approaches and research agenda.

The research covered 28 years of publications and summarised 497 articles, review papers and conference papers. Researchers concluded that IM highly correlates with the inventory turnover ratio and has no relation to firm performance. Further, TQM positively affects firm performance, but integrating IM and TQM will be a research scope for future study as none of the researchers previously covered this.

Due to the systematic literature review (SLR) and Bibliometric review, the study is limited to the Scopus and WoS (including Elsevier, Emerald Group Publishing, Taylor and Francis, Wiley, IEEE, Informs and SAGE) databases.

Being the research on a bibliometric and systematic review, relating IM practices with TQM practices would be the novelty of this paper.

Shareholder activism is gaining popularity across the globe especially in today’s context where the option of giving up and selling shares to exit the company has become obsolete. Hence, the purpose of this research paper is two-fold, firstly, to investigate the extent to which the minority shareholders of companies listed on the Stock Exchange of Mauritius adopt and make use of the various tools of activism; and secondly, to compare the UK laws on shareholder activism with that of Mauritius.

To achieve these objectives, this study adopted the qualitative research method. Primary data was collected by conducting a survey on minority shareholders of Mauritian listed companies to figure out the extent to which they resort to activism tools, while secondary data was collected through a qualitative legal, document and content analysis to scrutinise regulatory provisions and existing literature on the researched topic.

The results show a moderate implementation level of shareholder activism by the minority investors in Mauritius although it was noted that minority shareholders are more likely to resort to the internal tools of activism rather than external methods. Further to the comparative study conducted, this research recommends a more active participation of the Mauritian regulatory bodies, amendments to the Mauritius Code of Corporate Governance and Mauritius Companies Act and the establishment of a commission responsible for overseeing the exercise of shareholders’ powers and promoting derivative lawsuits among minority shareholders.

Few researchers like Beebeejaun and Koobloll (2018) analysed shareholder activism through the lens of corporate governance with the view of providing recommendations to bring amendments in the Mauritian corporate law landscape. However, to the best of the authors’ knowledge, no research has yet been effectuated on the extent to which shareholder activism is practised by the minority investors in developing countries, for which this existing study aims at filling in the research gap.

The purpose of the present work is identification and prioritization of barriers to Lean Six Sigma (LSS) implementation in Indian manufacturing industries in the context of Industry 4.0 (I4.0) to surmount the impediments in the path of successful implementation.

In total, 27 barriers identified through critical review of literature and expert's opinion are evaluated with Cronbach's alpha values including item-total correlations or corrected item-total correlations (CITC) using statistical tool. Finally, 20 barriers were analyzed and ranked employing Fuzzy Analytical Hierarchy Process (FAHP).

The study depicts that “Lack of leadership, advisory and monitoring,” “Lack of clarity about economic benefits” and “Lack of integration of LSS with smart tools/I4.0” are potential barriers to drive the path for proper implementation of LSS in Industry 4.0 with due consideration of its technologies in Indian manufacturing industries.

The study provides better knowledge platform for academicians and researchers about hidden aspects of LSS implementation barriers in view of advanced manufacturing technologies. This research will help the practitioners to design their business plans in implementing new quality improvement tools to get advantage in current competitive environment.

The barriers are selected based on literature and opinion from industry and academic experts. Five major criteria are decided after incorporating inputs. The ranking of the barriers is attained by well standard mathematical technique. This will enable the practitioners to design strategies to eliminate the hindrances in order to shape the right path for effective implementation of LSS approach in view of advanced manufacturing technologies.

The aim of this study is to comprehend the behavioural intention of females' perception toward smart healthcare technology. The study also examines the moderation effect of social influences between perceived smart healthcare technology and perceived usefulness among female users.

To test the model, this study collected data from female respondents (n = 913) responses. The data were analyzed by structural equation modeling (SEM) using Smart-PLS 3.2. To complement the findings from structural equation modeling, the study also conducted a post-hoc test via experimental research design. The authors also applied a t-test and PROCESS macro analysis to re-confirm the relationship mentioned above.

The findings revealed that perceived ease of use significantly mediates the relationship between females' perceived smart healthcare technology and intention to use. The findings also show that social influence moderates between smart healthcare technology and the perceived usefulness relationship.

Social influence is one of the major issues while adopting smart healthcare technology because the respondents perceived that they are accustomed to the technologies related to smart health once their surroundings and social environment influence them.

The current study is a pioneer in the context of a developing country and unique in that it makes two contributions: it extends previous research on smart health technology adoption in the healthcare business by considering females, and it gives a broad knowledge of the female healthcare consumers from emerging nations which can be useful for developing technology-driven healthcare services strategies.

This study aims to identify the factors influencing agile readiness in start-ups. Start-ups are being confronted with increased competition, customer demands, technological innovations and changes in the market environment. Adopting agile readiness for sustainable operations is a profitable and dependable way to improve the competition and reduce the number of failures of start-ups. The start-ups may investigate “how” after understanding the “whys.” The answers to these questions will be crucial to develop a strategy and a plan for luring clients, users, investors and partners. Therefore, this study will help in answering these crucial questions by using Total Interpretive Structural Modeling (TISM), whose main aim is to answer the key question of “what,” “how” and “why.” Using the “Total Interpretive Structural Modeling (TISM)” technique, this research tries to “describe,” “analyze” and “categorize” the agile readiness for sustainable operations enablers in start-ups.

Expert feedback and literature reviews from various start-ups led to the discovery of 10 enablers. In this study, the TISM technique was used to examine the inter-relationships between the enablers. The agile readiness for sustainable operations enablers was ranked and classified using the “Multiplication Applied to Classification (MICMAC)” technique. They were divided into four different categories: “autonomous,” “independent,” “linkage” and “dependent enablers.”

The results show that executive-level aid is the key agile readiness factor for sustainable operations. The next priority has been capability, experienced and skilled employees, market knowledge and environment agility. Leadership and clear vision have been given further priority. The next important is flexibility. The last and the least priority is given to receptive and strategic agility. This directional flow assists management in attaining adaptable sustainability, leading to continued growth in this dynamic environment.

The study focuses primarily on the agile readiness for sustainable operations of start-ups. This study offers a recommended list of crucial elements for start-ups, which may aid in creating guidelines for implementing agility for sustainable operations. This study provides academics with a TISM model that illustrates how start-ups can be ready to implement agility for sustainable operations. Future researchers could add more agility readiness variables to this study and validate this model across different start-ups.

Before implementing agile readiness for sustainable operations in start-ups, this study will aid managers and practitioners in the start-up business in understanding the relationships of enablers and identifying important readiness enablers.

The current study analyzes the agile readiness for sustainable operations in Start-ups. To the best of the authors’ knowledge, it is the first endeavor to use the “TISM approach” to examine the interrelationships across agile readiness for sustainable operations characteristics in start-ups.

Fused filament fabrication (FFF) is a type of additive manufacturing (AM) based on materials extrusion. It is the most widely practiced AM route, especially used for polymer-based rapid prototyping and customized product fabrication in relation to aerospace, automotive, architecture, consumer goods and medical applications. During FFF, part quality (surface finish, dimensional accuracy and static mechanical strength) is greatly influenced by several process parameters. The paper aims to study FFF parametric influence on aforesaid part quality aspects. In addition, dynamic analysis of the FFF part is carried out.

Interpretive structural modelling is attempted to articulate interrelationships that exist amongst FFF parameters. Next, a few specimens are fabricated using acrylonitrile butadiene styrene plastic at varied build orientation and build style. Effects of build orientation and build style on part’s ultimate tensile strength, flexure strength along with width build time are studied. Prototype beams (of different thickness) are fabricated by varying build style. Instrumental impact hammer Modal analysis is performed on the cantilever beams (cantilever support) to obtain the natural frequencies (first mode). Parametric influence on natural frequencies is also studied.

Static mechanical properties (tensile and flexure strength) are greatly influenced by build style and build orientation. Natural frequency (NF) of prototype beams is highly influenced by the build style and beam thickness.

FFF built parts when subjected to application, may have to face a variety of external dynamic loads. If frequency of induced vibration (due to external force) matches with NF of the component part, resonance is incurred. To avoid occurrence of resonance, operational frequency (frequency of externally applied forces) must be lower/ higher than the NF. Because NF depends on mass and stiffness, and boundary conditions, FFF parts produced through varying build style may definitely correspond to varied NF. This aspect is explained in this work.

The aim of this paper states that total productive maintenance (TPM) is an improvement tool which employs the effective utilization of employees in order to enhance the reliability of the equipment in consideration.

This paper identifies and evaluates the factors accountable for the adoption of TPM methodology in manufacturing organizations. Twenty-four factors affecting the TPM implementation are explored and categorized into five significant categories. Afterwards, these identified TPM factors have been evaluated by using a most popular Multi-criteria decision-making (MCDM) approach namely fuzzy pivot pairwise relative criteria importance assessment (F-PIPRECIA).

In this paper, through application of F-PIPRECIA, “Behavioural factor” is ranked first while “Financial factor” the last. Considering the sub-factors, “Top management support and commitment” is ranked first while “Effective use of performance indices” is ranked the last. A further sensitivity analysis indicates the factors that need higher level of attention.

The result of current research work may be exploited by the top administration of manufacturing enterprises for assessing their TPM adoption status and to recognize the frail links of TPM application and improve accordingly. Moreover, significant factors of TPM can be identified and deploy them successfully in their implementation procedure.

The conclusion obtained from this research enables the management to clearly understand the significance of each considered factor on the adoption of TPM in the organization and hence, provides effective utilization of resources.

In developing countries such as India, start-ups play an essential role in “industrial output,” “Gross Domestic Product ” and “employment creation.” Evidence suggests that pandemics have risen over the last century due to rising global travel and assimilation, urbanization, alterations in land use, and significantly larger exploitation of the natural environment. These trends are likely to continue and intensify. These pandemic episodes affect businesses, especially start-ups. Supplier selection is among the vital critical elements that start-ups must include in start-ups' strategy procedures during the pandemic episodes. This study's focus is to “identify,” “analyze,” and “categorize” the factors affecting supplier selection in start-ups during frequent pandemic episodes like coronavirus disease 2019 (COVID-19).

Through “literature review” and “experts' opinion” from various start-ups in India, ten affecting factors were identified. Total Interpretative Structural Modeling (TISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) were employed to analyze the interrelationship among the factors affecting the supplier selection on start-ups during frequent pandemic episodes, and these factors were ranked as “autonomous,” “independent,” “linkage,” and “dependent” factors.

The findings show that “performance history,” “service levels,” “technical capability,” and “financial stability” are the most critical factors affecting the supplier selection on start-ups during frequent pandemic episodes. The next importance should be safety and environmental concern” and “quality.”

The factors affecting supplier selection on start-ups during frequent pandemic episodes are the current focus of this study. This study is mainly performed on Indian start-ups and can be extended to other countries.

The start-ups can rely on this study to clearly understand the factors affecting the supplier selection on start-ups during frequent pandemic episodes.

There is no research regarding factors affecting supplier selection on start-ups during the COVID-19 emergencies. This research gap is filled by analyzing aspects linked to supplier selection in start-ups. This gap inspired the present study, which employs the “Total Interpretive Structural Modeling (TISM)” technique to uncover supplier selection determinants and investigate hierarchical interconnections among factors influencing/affecting supplier selection in start-ups during frequent pandemic episodes.

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.

This study aims to identify the enablers of human resource (HR) digitalization and HR analytics. This paper also aims to build a relationship map using interpretive structural modeling.

A systematic literature review is used to identify the key enablers of HR digitalization and HR analytics. Ten expert opinions have been taken from the key officials of IT firms located in New Delhi North Central Region.

This study is focused on the enablers of HR analytics. It is found that change management (CM) in the organization is the key enabler of implementing HR digitalization and analytics in an organization. However, other elements like learning culture, training and development, E-learning management and HR transformation (HRT) play a vital role in implementing HR analytics. It is also found that implementing artificial intelligence for HR practices is the ultimate goal for every organization.

Management teams in IT firms should focus on the continuous learning process in the organization. The CM should be expedited for digitalization and adoption of HR analytics. Managers must go through the ramification of HRT, which possesses diligence in HR analytics and artificial intelligence.

This study explicitly talks about the enablers of HR digitalization and HR analytics. It also explores the relationship between the enablers. This study also describes the driving and dependence power of all the enablers.