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Quality management practices (QMP) have stood as one of the critical strategic differentiators for enhancing firm performance. The production and manufacturing industry is the main driving force of economic growth and social development for any developed or developing country. This study aims to focus on two primary dimensions of QMP: soft quality management practices (SQMP) and hard quality management practices (HQMP) from the socio-technical system perspectives. Based on institutional theory perspectives, the study explores the impact of SQMP and HQMP on quality performance (QP), innovation performance (IVP) and financial performance (FP) in Indian oil processing organizations.

A proposed research model is validated using 289 cross-sectional survey data collected from the senior officials of oil processing firms in India. Covariance-based structural equation modeling is used to verify the proposed theoretical model.

SQMP, directly and indirectly, influenced QP and IVP while only indirectly to FP mediated through QP. HQMP directly impacted only QP while indirectly to IVP and FP mediated through QP.

Impact of organizational legitimacy in proper utilization or application of QMP in achieving the firm sustainable growth. The future study may address the following Research Question (RQ) also: How do QMP enhance the legitimacy of organizations operating in the oil processing industries? Are there specific mechanisms or pathways through which improved performance contributes to enhanced organizational legitimacy? How does legitimacy impact the success and sustainability of organizations, particularly, within the context of the oil processing industries? Are there regulatory requirements or industry certifications that organizations must adhere to in order to maintain legitimacy?

Similarly, manufacturing firms establish QMP of interaction and maintaining relationships with all the stakeholders, total employee empowerment and involvement, workforce commitment and workforce management, helping to control their reputations and maintain legitimacy (Li et al., 2023). Similarly, in the health industry, the health management information system (HMIS), which uses the DHIS2 platform, establishes that isomorphism legitimizes data QMP among health practitioners and, subsequently, data quality. Further, it was concluded that mimetic isomorphism led to moral and pragmatic legitimacy. In contrast, normative isomorphism led to cognitive legitimacy within the HMIS structure and helped to attain the correctness and timeliness of the data and reports, respectively (Msendema et al., 2023). Quality, flexibility and efficiency of Big Data Analytics through better storage, speed and significance can optimize the operational performance of a manufacturing firm (Verma et al., 2023).

The study provides the academician with the different dimensions of QMP. The study demonstrates how a firm develops multiple performance capabilities through proper QMP. Also, it shows how vital behavioral and managerial perspectives are to QMP and statistically solid tools and techniques. The study draws their importance to risk factors involved in the firms. Since the SQMP play a vital role, thus, emphasis on the behavioral dimension of quality requires more investigation and is in line with hard technological advancements in the quality field.

The study of the impact of HQMP and SQMP on performance is still not established. There are inconsistencies in the findings. The study of the impact of HQMP and SQMP in oil processing industries has not dealt with before. The effects of HQMP and SQMP on the firm’s FP have least been dealt. In context to the intended influence of QM implementation, QP has not been examined as a potential mediator between FP. Research carried out in the past is limited to American and European countries. However, a limited study was done in Asia, and no study has been conducted in the Indian context.

The paper aims to apply social practice theory to clarify the process of innovation design and delivery from one successful digital innovation: the building information modelling (BIM) risk library. The paper clarifies the practices surrounding construction innovation and provides a schema useful for practitioners and technology designers through a social practice analysis.

The paper applies Schatzki's “organisation of practice” concepts to a construction project innovation to clarify how the practice of innovation revolves around understandings, rules and teleoaffectivities (emotive behaviours). Sources for the study include notes from meetings, workshops with experts and the shared artefacts of innovation.

The practice of innovation design and delivery are clarified through a social practice analysis: a distinct “field of practice” and a “schema” of generalisable prescriptions and preferences for innovation delivery being presented.

The paper informs the practice and process of innovation design and delivery; the insights clarify how collective understandings and rules of use evolve over time, becoming formalised into contracts, agreements and workplans. Practically, processes whereby innovation “sayings” evolve into innovation “doings” are clarified: a schema detailing prescriptions and preferences of practitioners and developers being presented.

The social practice analysis of one successful construction innovation is an original contribution to the body of knowledge, adding a level of detail regarding innovation design and delivery often missing from reported research.

The current study used the social exchange theory to examine the dimensional impact of total quality management (TQM) on the organisational citizenship behaviour for the environment (OCBE) of employees through the mediatory role of environmental corporate social responsibility (ECSR).

The data were collected from 311 employees of ISO-14001-certified manufacturing firms in Pakistan. Both symmetrical partial least squares structural equation modelling (PLS-SEM) and asymmetrical fuzzy-set qualitative comparative analysis (fsQCA) methods were applied to test the proposed hypotheses to enhance the robustness of the results.

PLS-SEM results discovered that all dimensions of TQM, like process management, leadership, human resource management, customer focus, information and analysis and strategic planning, foster the OCBE through the mediation role of ECSR. The robustness of the findings was manifold when fsQCA results complemented the results by discovering that all six dimensions have been identified as sufficient conditions and some as necessary conditions to drive the OCBE.

The theoretical contribution of this study sheds light on TQM's function in boosting OCBE through the mediation of ECSR. Practically, the business managers may utilise TQM as a strategy to foster the OCBE in order to mitigate environmental damages of their organisations’ operations by instilling OCBE among the employees.

This study aims to investigate the adoption of the United Nations’ Sustainable Development Goals (SDGs) as the new performance perspective in cities. It also aims to understand how accounting for SDGs begins in city administrations by following Power’s (2015) fourfold development schema composed of policy object formation, object elaboration, activity orchestration and practice stabilization.

Focusing on a network of cities coordinated by the Finnish local government association, we analyzed the six largest cities in Finland employing a holistic multiple case study strategy. Our data consisted of Voluntary Local Reviews (VLRs), city strategies, budget plans, financial statements, as well as results of participant observations and semi-structured interviews with key individuals involved in accounting for SDGs.

We unveiled the SDG framework as an interpretive scheme through which cities glocalized sustainable development as a novel, simultaneously global and local, performance object. Integration of the new accounts in city management is necessary for these accounts to take life in steering the actions. By creating meaningful alignment and the ability to impact managerial practices, SDGs and VLRs have the potential to influence local actions. Our results indicate further institutionalization progress of sustainability as a performance object through SDG-focused work.

While prior research has focused mainly on general factors influencing the integration of the sustainability agenda, this study provides a novel perspective by capturing the process and demonstrating empirically how new accounts on SDGs are introduced and deployed in the strategic planning and management of local governments.

The main goal of the article is to determine the mediating role of HRM outcomes in the relationships between staffing the organization and company performance results and to establish whether there are any identifiable regularity in this scope in the pre-pandemic and pandemic period in the HQs and foreign subsidiaries of MNCs.

The empirical research included 200 MNCs headquartered in Central Europe. To capture the actual relations between the variables under study the raw data in the variables were adjusted with the efficiency index (EI). The Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to verify the research hypotheses and assess the mediating effects.

The research findings show that, with the exception of the HQs in the pandemic period, when staffing had a negative effect on the company performance results in quality, in other cases it had a positive effect on results in HRM, finance, innovativeness and quality, both in the pre-pandemic and pandemic period, although this effect was not always statistically significant. Furthermore, the company's performance results in HRM mediate positively the relationships between staffing and the other three categories of company performance results, regardless of the organizational level (HQs' or subsidiaries') and time period under consideration. Additionally, during the pandemic, the company's performance results in HRM mediate the relationships between staffing and the other company's performance results stronger than in the pre-pandemic time.

In addition to confirming the results of some other studies, the article also provides new knowledge. It determines the mediating role of HRM outcomes in the relationship between staffing and company performance results in finance, innovativeness and quality. Moreover, it identifies certain regularities in the four studied contexts, which is a novelty in this type of research. It also uses an innovative approach to including employee KPIs as the efficiency index in analyzing the relationships between the variables under study.

This study aims to provide an empirical investigation into rising capital flight and the role of institutional quality to mitigate its effect on the real sector in sub-Saharan Africa (SSA).

The study uses the system generalized method of moments and uses data spanning from 1989 to 2020 from 26 SSA countries.

The findings show that capital flight has no direct impact on the real sector while institutional quality adversely impacted the agricultural and industrial sectors. The study also found that institutional quality is unable to mitigate the effect of capital flight on the industrial sector.

This study investigates if institutional quality mitigates the impact of capital flight on the real sector proxied by industrial value-added and agriculture value-added.

The aim of this paper is to explore how multi-national corporations (MNCs) can effectively adopt artificial intelligence (AI) into their talent acquisition (TA) practices. While the potential of AI to address emerging challenges, such as talent shortages and applicant surges in specific regions, has been anecdotally highlighted, there is limited empirical evidence regarding its effective deployment and adoption in TA. As a result, this paper endeavors to develop a theoretical model that delineates the motives, barriers, procedural steps and critical factors that can aid in the effective adoption of AI in TA within MNCs.

Given the scant empirical literature on our research objective, we utilized a qualitative methodology, encompassing a multiple-case study (consisting of 19 cases across seven industries) and a grounded theory approach.

Our proposed framework, termed the Framework on Effective Adoption of AI in TA, contextualizes the motives, barriers, procedural steps and critical success factors essential for the effective adoption of AI in TA.

This paper contributes to literature on effective adoption of AI in TA and adoption theory.

Additionally, it provides guidance to TA managers seeking effective AI implementation and adoption strategies, especially in the face of emerging challenges.

To the best of the authors' knowledge, this study is unparalleled, being both grounded in theory and based on an expansive dataset that spans firms from various regions and industries. The research delves deeply into corporations' underlying motives and processes concerning the effective adoption of AI in TA.

The aim of this study is to empirically investigate the impact of marketing analytics capability on business performance from the perspective of RBV theory.

This study used a survey method to gather information from 225 food processing SMEs registered with the Ghana Enterprise Agency (GEA) in Ghana’s eastern region. A structural equation modeling (SEM) path analysis was used to assess the impact of marketing analytics capability (MAC) on the performance of SMEs.

The results of the study show that MAC significantly and positively affect the financial performance (FP), customer performance (CF), internal business process performance (IBPP) and learning and growth performance (LGP) of Ghanaian SMEs. The findings of this study also illustrated the significance of MAC determinants, including marketing analytics skills (MAS), data resource management (DRM) and data processing capabilities (DPC), in achieving SME success in Ghana.

The research’s conclusions give RBV theory strong credence. The results of this study also provide credence to previous research finding that SMEs should view MAC and its determinants (i.e. DRM, DPC, MAS) as a crucial strategic capability to improve their performance (i.e. FP, CF, IBPP, LGP). With regard to its contribution, this study broadens the body of knowledge on MAC and SME performance, particularly in the context of an emerging economy.

Pressures from non-profit sport organizations’ (NPSOs) external environment influence governance structures and processes. Thus, this study explores the impact of external factors on NPSO board decision making.

Using a sample of six NPSO boards (two national, four provincial/territorial), data were collected via 36 observations, 18 interviews, and over 900 documents. A thematic analysis was conducted via NVivo 12.

Results identified two external factors impacting NPSO board decision making: the sport system structure and general environment conditions. External factors impacted NPSO board decision making in terms of duration, flow, interaction, and scrutiny.

Results demonstrate the need for NPSO boards to engage in boundary-spanning activities whereby external information sources from stakeholders are incorporated to make informed decisions. Practically, NPSO boards should harness virtual meetings to continue their operations while incorporating risk management analyses to assess threats and opportunities.

Surprisingly little is known of the various methods of security analysis used by financial analysts with industry-specific knowledge. Financial analysts’ industry knowledge is a favored and appreciated attribute by fund managers and institutional investors. Understanding analysts’ use of industry-specific valuation models, which are the main value drivers within different industries, will enhance our understanding of important aspects of value creation in these industries. This paper contributes to the broader understanding of how financial analysts in various industries approach valuation, offering insights that can be beneficial to a wide range of stakeholders in the financial market.

This paper systematically reviews existing research to consolidate the current understanding of analysts’ use of valuation models and factors. It aims to demystify what can often be seen as a “black box”, shedding light on the valuation tools employed by financial analysts across diverse industries.

The use of industry-specific valuation models and factors by analysts is a subject of considerable interest to both academics and investors. The predominant model in several industries is P/E, with some exceptions. Notably, EV/EBITDA is favored in the telecom, energy and materials sectors, while the capital goods industry primarily relies on P/CF. In the REITs sector, P/AFFO is the most commonly employed model. In specific sectors like pharmaceuticals, energy and telecom, DCF is utilized. However, theoretical models like RIM and AEG find limited use among analysts.

This is the first paper systematically reviewing the research on analyst’s use of industry-specific stock valuation methods. It serves as a foundation for future research in this field and is likely to be of interest to academics, analysts, fund managers and investors.