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The purpose of this paper is to identify integrated solutions business as the first generation of servitized offerings and modular solution offerings as the second development phase in servitization of original equipment manufacturers. This study examines how the servitized manufacturer, Kone, moves from integrated solutions to modular solutions business and develops the requisite capabilities to design, produce and implement modular solution offerings.

The paper reports a longitudinal case study of a provider of integrated solutions installed in buildings. During the ten years studied, the manufacturer implemented a strategic initiative to modularize its integrated solutions offering.

The firm’s transition to modular solutions progressed through three major capability development phases: solutions based on ad hoc integration, smart solutions based on modular design and through-chain modularity. The modular structure aims at fostering the efficiency of the solution offering and the associated production system.

Leveraging the benefits of modularity calls for an aligned combination of strategic, operational and technical capabilities contributing to the integration of resources in a modular production system for the solution providers’ competitive performance.

The study reports how a solution provider can develop the operational capabilities to integrate the core and peripheral components into the solution, and orchestrate the modular production system.

This study is a rare longitudinal analysis of how a manufacturer builds a modular offering, the solution platform and the required competitive capabilities to provide the solution.

Digital servitization concerns how manufacturers utilize digital technologies to enhance their provision of services. Although digital servitization requires that manufacturers possess new capabilities, in contrast to strategic (or dynamic) capabilities, little is known about how they develop the required operational capabilities. The paper investigates the mechanisms for developing operational capabilities in digital servitization.

This paper presents an exploratory study based on 15 large manufacturers operating in Europe engaged in digital servitization.

Three operational capability development mechanisms are set out that manufacturers use to facilitate digital servitization: learning (developing capabilities in-house), building (bringing the requisite capabilities into the manufacturer), and acquiring (utilizing the capabilities of other actors). These mechanisms emphasize exploitation and exploration efforts within manufacturers and in collaborations with upstream and downstream partners. The findings demonstrate the need to combine these mechanisms for digital servitization according to combinations that match each manufacturer’s traditional servitization phase: (1) initial phase - building and acquiring, (2) middle phase - learning, building and acquiring, and (3) advanced phase - learning and building.

This study reveals three operational capability development mechanisms, highlighting the parallel use of these mechanisms for digital servitization. It provides a holistic understanding of operational capability development mechanisms used by manufacturers by combining three theoretical perspectives (organizational learning, absorptive capacity, and network perspectives). The paper demonstrates that digital servitization requires the significant application of building and acquiring mechanisms to develop the requisite operational capabilities.

Insufficient productivity development in the global and Finnish infrastructure sectors indicates that there are challenges in genuinely achieving the goals of resource efficiency and digitalization. This study adapts the approach of capability maturity model integration (CMMI) for examining the capabilities for productivity development that reveal the enablers of improving productivity in the infrastructure sector.

Civil engineering in Finland was selected as the study area, and a qualitative research approach was adopted. A novel maturity model was constructed deductively through a three-step analytical process. Previous research literature was adapted to form a framework with maturity levels and key process areas (KPAs). KPA attributes and their maturity criteria were formed through a thematic analysis of interview data from 12 semi-structured group interviews. Finally, validation and refinement of the model were performed with an expert panel.

This paper provides a novel maturity model for examining and enhancing the infrastructure sector’s maturity in productivity development. The model brings into discussion the current business logics, relevance of lifecycle-thinking, binding targets and outcomes of limited activities in the surrounding infrastructure system.

This paper provides a new approach for pursuing productivity development in the infrastructure sector by constructing a maturity model that adapts the concepts of CMMI and change management. The model and findings benefit all actors in the sector and provide an understanding of the required elements and means to achieve a more sustainable built environment and effective operations.

Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities. Despite the endless possibilities, organizations face operational challenges in harvesting the value of ML-based capabilities (MLbC), and current research has yet to explicate these challenges and theorize their remedies. To bridge the gap, this study explored the current practices to propose a systematic way of orchestrating MLbC development, which is an extension of ongoing digitalization of organizations.

Data were collected from Finland's Artificial Intelligence Accelerator (FAIA) and complemented by follow-up interviews with experts outside FAIA in Europe, China and the United States over four years. Data were analyzed through open coding, thematic analysis and cross-comparison to develop a comprehensive understanding of the MLbC development process.

The analysis identified the main components of MLbC development, its three phases (development, release and operation) and two major MLbC development challenges: Temporal Complexity and Context Sensitivity. The study then introduced Fostering Temporal Congruence and Cultivating Organizational Meta-learning as strategic practices addressing these challenges.

This study offers a better theoretical explanation for the MLbC development process beyond MLOps (Machine Learning Operations) and its hindrances. It also proposes a practical way to align ML-based applications with business needs while accounting for their structural limitations. Beyond the MLbC context, this study offers a strategic framework that can be adapted for different cases of digital transformation that include automation and augmentation of work.

The purpose of this study is to elaborate on how analytics capability develops within the PSM function. This study is an in-depth exploration of how analytics capability develops within the purchasing and supply management (PSM) function.

A multiple case study was conducted of the PSM function of six case firms, in which primary data were collected through semi-structured interviews with PSM analytics stakeholders. The data were analyzed based on an analytics capability framework derived from the literature. Cases were chosen based on them having advanced PSM practices and ongoing analytics projects in the PSM area.

The findings shed light on how the firms develop their analytics capability in the PSM functional area. While we identify several commonalities in this respect, the authors also observe differences in how firms organize for analytics, bringing analytics and PSM decision-makers together. Building on the knowledge-based view of the firm, The authors offer a theoretical explanation of our observations, highlighting the user-driven side of analytics development, which has largely been unrecognized by prior literature. The authors also offer an explanation of the observed dual role that analytics takes in cross-functional initiatives.

The exploratory nature of our study limits the generalizability of our results. Further, our limited number of cases and interviewees indicate that there is still much to explore in the phenomenon of developing analytics capability.

Our findings can help firms gain a better understanding of how they could develop their analytics capability and what issues they need to consider when seeking leveraging data through analytics for PSM decisions.

This paper is, to the best knowledge of the authors, the first empirical study of analytics capability in PSM.

This study aims to focus on creating sales capability as part of new product development (NPD). The aim is to define generic requirements for building sales capability as a part of NPD and to propose a necessary process by defining key activities for sales readiness.

An inductive and qualitative research method was used to construct a sales capability creation process based on a current state analysis in seven companies.

The results indicate that the status of companies’ sales-related planning varies during the NPD, and the related activities are not systematically managed. Considering sales early is necessary to enable a smooth and cost-efficient start of sales, and to avoid unnecessary delays and problems in other functions. At the same time, the companies recognise the need for improvement.

This paper presents a potential process including systematic activities for creating sales capability in conjunction with product development, which is novel to the literature. The proposed process is applicable in aligning industrial company needs.

This paper examines the moderating effect of environmental capability development on the relationship between supply chain integration and both environmental and financial performance.

The authors use empirical data collected from three diverse sources in the horticultural marketing sector. A total of 97 responses were used. An ordered logit analysis and ordinary least squares (OLS) regression were employed to test the hypotheses.

The results confirm that firm environmental capability development enhances the effects of supply chain integration on firm environmental performance. Additionally, supplier integration and environmental capabilities may be considered firm strategic capabilities that are positively related to financial performance. Thus, public policies should encourage the development of firms' individual environmental capabilities and supply chain integration to improve environmental sustainability.

This study recognizes the importance of environmental capability development as a strategic objective and its fundamental role as a complementary capability with supply chain integration. This paper contributes by empirically analyzing how firms along the supply chain can promote environmental sustainability through the development of environmental and integration capabilities.

The purpose of this paper is to report on research into the impact of two sequential dimensions of strategic purchasing – purchasing recognition and purchasing involvement – on the development and deployment of dynamic capabilities. The authors also examine how such dynamic capabilities impact on both cost and innovation performance, and how their effects differ for service as opposed to manufacturing firms.

The authors test hypotheses using structural equation modeling of survey data from 309 manufacturing and service firms.

From a dynamic capability perspective, the analysis supports the positive relationships between purchasing recognition, purchasing involvement, and dynamic capability in the form of knowledge scanning. The authors also find support for the positive impact of knowledge scanning on both cost and innovation performance. From a contingency perspective, data supports hypothesized differences caused by industry, whereby service-based firms experience stronger positive linkages in our model than manufacturing-based firms. Finally, emerging from the data, the authors explore a re-enforcing effect from cost performance to purchasing involvement, something that is in line with the dynamic capabilities perspective but not typically addressed in operations management (OM) research.

The research offers a number of theoretical and managerial contributions, including being one of a relative few examples of empirical assessment of dynamic capability development and deployment; examining the enablers of dynamic capability in addition to the more commonly addressed performance effect; assessing the contingency effect of firm type for dynamic capabilities; and uncovering a return (re-enforcing) effect between performance and enablers of dynamic capabilities.

In this paper, the authors aim to introduce international dynamic marketing capabilities (IDMCs) theoretically derived from marketing capabilities (MCs), dynamic marketing capabilities (DMCs) and international marketing capabilities (IMCs) and provide a novel conceptualization of the concept by applying a holistic view of the international enterprise.

This is a literature review that maps the current research on MCs, DMCs and IMCs and serves as a basis for the theoretical conceptualization of a novel IDMCs concept as well as for the identification of research gaps and the development of future research directions on this phenomenon.

Existing typologies of MCs, DMCs and IMCs are classified into four categories: strategic, operational, analytical and value creation capabilities. A new typology of IDMCs is proposed, consisting of digital MC and dynamic internationalization capability as strategic capabilities, agile IMC, IM excellence and absorptive capability in IM as operational capabilities, IM resilience capability, IM knowledge management capability, AI-enabled IDMC and Industry 4.0-enabled IDMC as analytical capabilities, and ambidextrous IM innovation capability as value creation capability. Finally, the authors identify research gaps and develop research questions that open future research avenues for the coming years.

This paper offers a novel view of MCs, DMCs and IMCs and argues that, in contrast to the majority of previous research, a comprehensive understanding of these is only possible if all levels are considered simultaneously: the strategic, the operational, the analytical and the value creation level. A new conceptualization and typology of IDMCs follows this logic.

This paper investigated the organizational adoption of big data analytics (BDA) in the context of supply chain planning (SCP) to conceptualize how resources are orchestrated for organizational BDA adoption and to elucidate how resources and capabilities intervene with the resource management process during BDA adoption.

This research elaborated on the resource orchestration theory and technology innovation adoption literature to shed light on BDA adoption with multiple case studies.

A framework for the resource orchestration process in BDA adoption is presented. The authors associated the development and deployment of relevant individual, technological and organizational resources and capabilities with the phases of organizational BDA adoption and implementation. The authors highlighted that organizational BDA adoption can be initiated before consolidating the full resource portfolio. Resource acquisition, capability development and internalization of competences can take place alongside BDA adoption through structured processes and governance mechanisms.

A relevant discussion identifying the capability gap and provides insight into potential paths of organizational BDA adoption is presented.

The authors call for attention from policymakers and academics to reflect on the changes in the expected capabilities of supply chain planners to facilitate industry-wide BDA transition.

This study opens the black box of organizational BDA adoption by emphasizing and scrutinizing the role of resource management actions.