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Big data is one of the most demanding topics in contemporary marketing research. Despite its importance, the big data-based strategic orientation in international marketing is yet to be formed conceptually. Thus, the purpose of this study is to systematically review and propose a holistic framework on big data-based strategic orientation for firms in international markets to attain a sustained firm performance.

The study employed a systematic literature review to synthesize research rigorously. Initially, 2,242 articles were identified from the selective databases, and 45 papers were finally reported as most relevant to propose an integrative conceptual framework.

The findings of the systematic literature review revealed data-evolving, and data-driven strategic orientations are essential for performing international marketing activities that contain three primary orientations such as (1) international digital platform orientation, (2) international market orientation and (3) international innovation and entrepreneurial orientation. Eleven distinct sub-dimensions reflect these three primary orientations. These strategic orientations of international firms may lead to advanced analytics orientation to attain sustained firm performance by generating and capturing value from the marketplace.

The study minimizes the literature gap by forming knowledge on big data-based strategic orientation and framing a multidimensional framework for guiding managers in the context of strategic orientation for international business and international marketing activities. The current study was conducted by following only a systematic literature review exclusively in firms' overall big data-based strategic orientation concept in international marketing. Future research may extend the domain by introducing firms' category wise systematic literature review.

The study has proposed a holistic conceptual framework for big data-driven strategic orientation in international marketing literature through a systematic review for the first time. It has also illuminated a future research agenda that raises questions for the scholars to develop or extend theory in this area or other related disciplines.

SOME kinds of chrome‐molybdenum steels widely employed in the construction of aeroplanes, the chrome‐manganese‐silicon steels introduced comparatively recently and even some carbon steels with a higher content than 0·2 per cent. carbon show minute cracks after welding with oxy‐acctylene, even when the actual operation of welding is carried out faultlessly. This tendency is described as “weld‐crackability,” cracking occurring at high temperatures. At first, micro‐fractures form, causing in turn the formation of cracks that are visible at a temperature still high enough to cover their surface with a dark bluish flux. These cracks occur not only in the weld itself but also in the whole of the region affected by the thermic influence of the flame. It is characteristic that welding by an electric are does not produce this phenomenon.

The paper aims to examine how a professional development school-district (PDS-D) partnership, enacting an improvement science stance, collectively explored social-emotional learning (SEL) during collaboratively designed professional learning experiences.

This qualitative study, guided by an improvement science orientation, enacted an iterative research design. Data sources consisted of anecdotal field notes and artifacts from 12 professional learning sessions. Using a constant comparative method, the authors applied an inductive thematic analysis to identify salient themes across data related to teacher wonderings and identified goals.

The paper illuminates teachers' voices while highlighting information gleaned from participant wonderings, their identified goals and how this information informed the iterative development of future professional learning experiences within a district-university partnership.

Due to the chosen research approaches and limited number of participants, the research results may lack generalizability.

This paper provides original insight into collaborative development of recursive professional learning experiences within partnership spaces.

Primary teachers play a vital role in fostering pupils' successful futures. Therefore, gaining knowledge of primary teacher students' learning processes, including the achievement of information-seeking skills, is crucial. The aim of this paper is to understand better the interplay between cognitive appraisals and emotions in the constructivist process of learning and achieving information-seeking skills.

In-depth semi-structured interviews were conducted with six Swedish primary teacher students. The analysis of qualitative data was deductive and theory-driven, guided by Kuhlthau's information search process model, Scherer's semantic space of emotions and Pekrun's control-value theory of achievement emotions.

Anger/frustration, enjoyment and boredom were identified as activity emotions and anxiety, hopelessness and hope as prospective outcome emotions. The retrospective outcome emotions found were pride, joy, gratitude, surprise and relief. The appraisals eliciting the achievement emotions were the control appraisals uncertainty/certainty (activity and prospective outcome) and oneself/other (retrospective), and value appraisals negative/positive intrinsic motivation (activity) and failure/success (prospective and retrospective). The interplay between appraisals and emotions was complex and dynamic. The processes were individually unique, non-linear and iterative, and the appraisals did not always elicit emotions.

The study has theoretical and methodological implications for information behaviour research in its application of appraisal theories and the Geneva affect label coder. In addition, it has practical implications for academic librarians teaching information-seeking skills.

Influencer marketing mediated by social media is prevalent in social commerce. Micro-, meso- and macro-influencers all play an irreplaceable role in marketing. The purpose of this paper is to explore how companies with limited budgets choose influencers according to products' various levels of brand familiarity.

This study constructs an evolutionary game model of influencer marketing based on evolutionary game theory on complex networks. This model initiates various networks to demonstrate how influencers disseminate information and constructs update mechanisms to depict how individuals react to this information based on individuals' information utility and friends' strategies.

Simulation results suggest that companies should invest more in macro-influencers than in meso-influencers, however investing all in macro-influencers is not a good choice. The investment in meso-influencers will increase as brand familiarity decreases, whereas it will not exceed investment in macro-influencers. Furthermore, the accumulation of micro-influencers can accelerate the marketing process.

This study examines the combined effects of micro-influencers, meso-influencers and macro-influencers in marketing by simulating the marketing process initiated by influencers on social media.

This study identifies and characterizes configurations of generic business models for logistics service providers (LSPs) in the context of industrial additive manufacturing (AM). A literature-based framework of the AM service supply chain (SC) is developed to embed the generic configurations in their SC context.

Following an exploratory research design, 17 interviews were conducted with LSPs, LSPs' potential partners and customers for industrial AM services.

Six generic configurations are identified, the LSP as a Manufacturer, Landlord, Logistician, Connector, Agent and Consultant. The authors outline how these configurations differ in the required locations, partners and targeted customer segments.

The current discussion of reshoring and shorter, decentralized AM SCs confronts LSPs with novel challenges. This study offers guidance for managers of LSPs for designing business models for industrial AM and raises awareness for LSPs' resource and SC implications.

This study contributes to the scarce literature on AM business models for LSPs with in-depth empirical insights. Based on the six identified configurations, this study sets the ground for theorizing about the business models, in particular, the value creation, value proposition and mechanisms for value capture of the business models. In addition, this study suggests how the generic configurations fit the features of specific types of LSPs.

This study focuses on leadership in organizations where big data analytics (BDA) is an essential component of corporate strategy. While leadership researchers have conducted promising studies in the field of digital transformation, the impact of BDA on leadership is still unexplored.

This study is based on semi-structured interviews with 33 organizational leaders and subject-matter experts from various industries. Using a grounded theory approach, a framework is provided for the emergent field of BDA in leadership research.

The authors present a conceptual model comprising foundational competencies and higher order roles that are data analytical skills, data self-efficacy, problem spotter, influencer, knowledge facilitator, visionary and team leader.

This study focuses on BDA competency research emerging as an intersection between leadership research and information systems research. The authors encourage a longitudinal study to validate the findings.

The authors provide a competency framework for organizational leaders. It serves as a guideline for leaders to best support the BDA initiatives of the organization. The competency framework can support recruiting, selection and leader promotion.

This study provides a novel BDA leadership competency framework with a unique combination of competencies and higher order roles.

This paper aims at identifying the main contributions of Industry 4.0 (I4.0) technologies to the enhancement of knowledge management (KM).

A scoping review based on two stages was carried out. In the first stage, a numerical and descriptive analysis was conducted. In the second stage, the latent content of those papers was explored through a qualitative analysis, in which papers were assessed regarding the outcome of the implementation of ten I4.0 technologies on 14 KM abilities and 6 KM processes.

Six technologies (e.g. Internet of Things (IoT), big data, cloud computing, simulation, visualisation and industrial robot) were claimed to have a significant contribution on KM, especially for creation, organisation, dissemination and application processes. Overall, results indicated that technologies can significantly contribute to KM, although the extent of such contribution varies across technologies, learning levels, KM processes and abilities.

Existing studies in I4.0 fall short in exploring how embodied knowledge is articulated in practice, especially regarding opportunities to use new technological alternatives in favour of knowledge and learning development. This study complements the existing literature on I4.0 by identifying which technologies can contribute to KM. Also, a framework was proposed to examine the contribution of I4.0 technologies to KM at individual, team, and organisational levels.

This paper aims to present the methodology for designing a system providing comprehensive data about the UK’s museums and enabling research into the history, status and long-term development of the entire sector.

The authors have devised and applied an iterative methodology to deliver a knowledge base, web application and website through which these and related resources are publicly accessed, allowing incorporation of the requirements of user stakeholders drawn from across the UK museum sector.

The methodology has enabled the elicitation of usage scenarios, research questions and feedback from a broad range of user stakeholders, allowing the system to be successfully delivered within the time and staffing constraints of a single publicly-funded research project. Feedback received from external evaluators and users of the system has been overwhelmingly positive.

The system includes the only comprehensive data set of the UK’s museums and is enabling new research by museum studies scholars and museum professionals. The methodology can inform other projects aiming to create specialist knowledge resources involving a wide range of user stakeholders, particularly within constrained time and staffing resources.

This study aims to demonstrate how Carney’s ladder of analytical abstraction is used to examine the motivations of banks for reporting human capital (HC) information.

The authors use semi-structured interviews of senior bank employees at eight large New Zealand banks. They analyse the managers’ views using a constructive mapping of responses applying Carney’s ladder of analytical abstraction. The findings are interpreted from a stakeholder theory perspective.

The authors find that the New Zealand banks report on HC to manage reputation, strengthen employee relationships and achieve competitive advantages. The results suggest that banks engage in opportunistic reporting to distract external stakeholders while advancing their interests.

The study will guide researchers in the use of Carney’s ladder of analytical abstraction in analysing qualitative data.

This study provides insights for businesses to improve the consistency and quality of HC reporting and ensure that the information needs of broader stakeholder groups are met.

Some previous voluntary reporting studies analyse their data using inductive analysis. The authors use Carney’s ladder of analytical abstraction as a framework to guide our inductive analysis.