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Drawing on the cumulative capability perspective, this study tests the sand cone model of the triple-A supply chain (SC) (i.e. AAA: SC-alignment, SC-adaptability, SC-agility), including its financial performance implications. Besides, this study investigates social capital as AAA enabler.

Structural equation modeling and bootstrapping analysis are used to examine hypotheses using data from 216 companies in China that capture firms’ supply chain management practices in relation to their major suppliers.

We identified a cumulative sand cone sequence of three As: alignment-adaptability-agility to effectively develop a triple-A SC. Furthermore, based on this sequence, SC adaptability can enhance financial performance indirectly through SC agility, and SC alignment can improve financial performance indirectly through SC adaptability and SC agility, which directly and positively affects financial performance. Furthermore, cognitive, structural, and relational capital play different roles in improving AAA.

This study contributes to triple-A SC literature by identifying the cumulative sand cone sequence of alignment-adaptability-agility and thus further extends the cumulative capability perspective in operations and supply chain management. Besides, this study: (1) deepens our understanding of performance implications of triple-A SC capabilities based on the sand cone model; (2) contributes to revealing social capital as an important enabler of triple-A SC capabilities from the complex adaptive system perspective; (3) specifies difference in the pattern of triple-A SC sand cone model across different levels of market turbulence.

This paper presents the design and implementation of a maturity model for assessing the cost measurement and management capabilities of organisations. Beyond capability evaluation, the model is also designed to provide guidance for improving the competitiveness of value chains across a focal company and its suppliers. Thus, it can also be used to improve inter-organisational performance.

The research, which is interventionist in nature, was developed through a collaboration between the authors and two manufacturing companies that co-funded the design and development of the model. The study follows a constructive research approach, applying established principles, instructions and known development steps to the design and implementation of a maturity model.

The paper introduces a maturity model centred on cost measurement and management capabilities by presenting its constituent parts and functioning. The model is called Cost Management Maturity Model (CMMM).

CMMM is a managerial tool that companies can use to assess the maturity of their cost measurement and management capabilities and then derive directions for improvement. It is also a tool that managers can use in the context of inter-organisational relationships to align the cost-related capabilities of a network of companies, such as a supply chain. This has the result of strengthening inter-organisational collaborations to reduce costs and improve value creation.

This paper presents an original four-level, pyramid-shaped maturity model that advances prior endeavours to this end within the realm of managerial costing. Unlike existing models, CMMM boasts a wider scope of inquiry that includes attention to cost management and inter-organisational contexts. It also provides a structured and replicable yet flexible maturity evaluation method founded on a questionnaire and an associated scoring method.

This paper investigates how a firm’s organizational culture profile (configuration of organizational culture types) influences the effectiveness of operations management (OM) practices in improving their targeted outcomes.

We developed alternative hypotheses based on contingency and paradox perspectives to predict the effectiveness of OM practices in dominant (one prevalent organizational culture type) vs eclectic (opposing organizational culture types at a similar level) organizational culture profiles. They were tested using data from over 7,000 respondents across 330 manufacturing plants in 15 countries.

Consistent with contingency theory, OM practices oriented toward innovation are more efficacious in plants with an adhocracy-dominant organizational culture profile and practices targeting supply chain (SC) control are less effective in a clan-dominant organizational culture profile. Consistent with paradox theory, OM practices oriented toward efficiency or SC control are more effective in plants with an eclectic organizational culture profile.

This study offers relevant practical implications regarding the effectiveness of various OM practices, whether they are used in an aligned dominant organizational culture profile or in an eclectic organizational culture profile.

Previous research on organizational culture provides a limited understanding of the effectiveness of OM practices in the presence of strategic tensions, such as opposing organizational cultures or opposing targeted outcomes. This research concludes that the validity of the contingency or paradox perspective depends on strategic tensions faced, with important implications for research and practice.

This study aims to identify the key factors that influence household pro-environmental behaviors (HPEBs) and explore the differences caused by the same influencing factors between household waste management behavior (HWM) and household energy-saving behavior (HES).

A meta-analysis was conducted on 90 articles about HPEBs published between 2009 and 2023 to find the key factors. HPEBs were further categorized into HWM and HES to investigate the difference influenced by the above factors on two behaviors. The correlation coefficient was used as the unified effect size, and the random-effect model was adopted to conduct both main effect and moderating effect tests.

The results showed that attitude, subjective norms, and perceived behavioral control all positively influenced intention and HPEBs, but their effects were stronger on intention than on HPEBs. Intention was found to be the strongest predictor of HPEBs. Subjective norms were found to have a more positive effect on HES compared to HWM, while habits had a more positive effect on HWM. Furthermore, household size was negatively correlated with HWM but positively correlated with HES.

The same variables have different influences on HWM and HES. These results can help develop targeted incentives to increase the adoption of HPEBs, ultimately reducing household energy consumption and greenhouse gas emissions and contributing to the mitigation of global warming.

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.

Responding to calls for deeper analysis of the conceptual foundations of service infusion in manufacturing, this paper examines the underlying assumptions that: (i) manufacturing firms incorporating services follow a pathway, moving from pure-product to pure-service offerings, and (ii) profits increase linearly with this process. We propose that these assumptions are inconsistent with the premises of behavioural and learning theories.

Machine learning algorithms are applied to test whether a successive process, from a basic to a more advanced offering, creates optimal performance. The data were gathered through two surveys administered to USA manufacturing firms in 2021 and 2023. The first included a training sample comprising 225 firms, whilst the second encompassed a testing sample of 105 firms.

Analysis shows that following the base-intermediate-advanced services pathway is not the best predictor of optimal performance. Developing advanced services and then later adding less complex offerings supports better performance.

Manufacturing firms follow heterogeneous pathways in their service development journey. Non-servitised firms need to carefully consider their contextual conditions when selecting their initial service offering. Starting with a single service offering appears to be a superior strategy over providing multiple services.

The machine learning approach is novel to the field and captures the key conditions for manufacturers to successfully servitise. Insight is derived from the adoption and implementation year datasets for 17 types of services described in previous qualitative studies. The methods proposed can be extended to assess other process-based models in related management fields (e.g., sand cone).

The purpose of this paper is to investigate how different manufacturing technologies are bundled together and how these bundles influence operations performance and, indirectly, business performance. With the emergence of Industry 4.0 (I4.0) technologies, manufacturing companies can use a wide variety of advanced manufacturing technologies (AMT) to build an efficient and effective production system. Nevertheless, the literature offers little guidance on how these technologies, including novel I4.0 technologies, should be combined in practice and how these combinations might have a different impact on performance.

Using a survey study of 165 manufacturing plants from 11 different countries, we use factor analysis to empirically derive three distinct manufacturing technology bundles and structural equation modeling to quantify their relationship with operations and business performance.

Our findings support an evolutionary rather than a revolutionary perspective. I4.0 technologies build on traditional manufacturing technologies and do not constitute a separate direction that would point towards a fundamental digital transformation of companies within our sample. Performance effects are rather weak: out of the three technology bundles identified, only “automation and robotization” have a positive influence on cost efficiency, while “base technologies” and “data-enabled technologies” do not offer a competitive advantage, neither in terms of cost nor in terms of differentiation. Furthermore, while the business performance impact is positive, it is quite weak, suggesting that financial returns on technology investments might require longer time periods.

Relying on a complementarity approach, our research offers a novel perspective on technology implementation in the I4.0 era by investigating novel and traditional manufacturing technologies together.

Given the sudden increase in plant investments across the manufacturing sector due to recent disruptions in the global supply chain caused by the COVID pandemic, the Ukraine/Russian war, ocean piracy incidents, and others, there is a need to strategically align the investments decisions with the overall business strategy. This study aims to establish whether strategic alignment enhances the effect of plant investments on operational performance.

Using the fifth version of the Global Manufacturing Research Group (GMRG V) dataset, we employ a structural equation model (SEM) to establish the moderating role of strategic alignment in plant investments-operational performance relationships.

The results suggest that strategic alignment enhances the positive effect of plant investments on operational performance, especially in cost, delivery, flexibility, and innovation. However, we found partial support for the moderating role of strategic alignment on quality performance.

Although the study was based on the GMRG global dataset and numerous papers have been published using the same dataset, the use of a convenience sample on a select group of companies may limit the generalizability of the results. With the increase in new plant investments in computer chip manufacturing, electronics, and electrical in recent years, the findings could help corporate executives maximize the benefits of their investment decisions. Companies should ensure that their plant investment decisions are strategically aligned with their overall business strategy to achieve optimal outcomes.

With the increase in new plant investments in computer chip manufacturing, electronics, and electrical in recent years, the findings could help corporate executives maximize the benefits of their investment decisions. Companies should ensure that their plant investment decisions are strategically aligned with their overall business strategy to achieve optimal outcomes.

The study comprehensively demonstrates that the extent of improvement in operational performance depends on how closely plant investment decisions align with the overall company strategy. Manufacturers should align major investment decisions with competitive priorities driven by market requirements to enhance operational performance.

Project management scholars and practitioners have long debated how best to harness social interactions to optimise knowledge exchange and enhance stakeholder alignment and value. This study aims to assist project managers to understand and manage fuzziness and create enduring front-end value. It views the project life cycle as a potential source of co-created value. The paper uses a social capital lens to provide a deeper understanding of the project front-end; it uses a three-dimensional view (structural, relational, cognitive) to explore how stakeholder social capital can overcome front-end fuzziness to enhance decision-making and, thus, value creation.

Semi-structured interviews were conducted with senior managers from teleconnections companies, which, when combined with secondary data, established the impact, nature and dimensions of social capital within a project management setting.

The research found that social capital can help to reduce complexity, uncertainty and equivocality in the early stages of projects, making them more clearly defined and thus helping to create greater stakeholder value in the later stages of the project. A surprising finding was that some project team members engaged in intentional equivocality to try to promote their own benefits rather than those of the organisation.

This paper reconceptualises the impact of social capital on stakeholder value creation in the front-end of projects. The paper contributes to a more holistic view of the front-end of project management, focusing social capital to reduce the sources of front-end fuzziness.