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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.

Purpose – This chapter explores a traditional mode of ethnography referred to as ‘realist ethnography’ as it relates to sport and physical culture (SPC) research.

Design/methodology/approach – The chapter discusses different approaches to ethnography, but principally addresses a realist ethnography I conducted on Ashtanga yoga in Canada.

Findings – I discuss how data evolved from the realist ethnographic method, and outline the manner in which ethnographic research is as a ‘way of life’. The chapter concludes that the realist ethnographic method is not untenable, as some authors suggest, but rather a viable and exciting mode of knowledge production in the SPC field.

Originality/value – The chapter is original work. It makes a case for the retention of realist ethnographies in our methodological lexicon, and illustrates the empirical process of writing culture. It also endeavours to engage students and scholars alike regarding the value of ethnographic methods more broadly.

Purpose – This chapter explores various approaches to historical methods as they relate to sport and physical culture research.

Design/methodology/approach – The chapter discusses various paradigmatic approaches to historical methods (reconstructionist, constructionist and deconstructionist) and takes up current debates related to archives, newspapers, photographs and oral history as they relate to the method. Drawing on these discussions, I outline various approaches to designing a sport and physical culture project using historical methods, focusing on my work on women's industrial sport in the 1920s and early 1930s.

Findings – I discuss how data evolved from the method and how I made choices about the inclusion and exclusion of materials. The chapter concludes that historical methods are tedious, complex and messy but also exciting and insightful ways to do research. I also conclude by encouraging the researcher to be reflexive and aware of one's ‘positionality’ as a researcher and embrace the historical process.

Originality/value – The chapter is original work. It is not so much a prescriptive ‘how-to’ guide for historical research, but it works to take up current debates in historical methods. It also endeavours to engage students and scholars alike as they consider their research projects and the potential value of historical methods.

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.

This chapter discusses the different types of researcher/participant relationship described in the case study chapters, alongside the extent to which the projects were (and could be) pre-defined in terms of structure and expected outcomes. The case studies ranged from secondary data analysis methods with no researcher/participant contact, those with structured one-off interviews, those with more ongoing, but still researcher-led, relationships between researcher and participant, to more ethnographic and participatory research where relationships were negotiated between researcher and participant and, in some cases, led by the participants. This chapter highlights that researcher/participant relationships lie parallel to the structure of the project and the extent to which the outcomes are pre-defined. Despite the range of types of relationship, however, all the case studies highlighted the value of trust in those relationships, for participants to feel happy to share the details of their personal lives beyond that which is usually visible in the formal education setting of school. Edwards' (2017a) concepts of relational agency, relational expertise and common knowledge are used to help explain why these relationships matter in research on out-of-school learning – to understand activities that we do not know about, which take places in spaces that we are unfamiliar with.

We analyze spatio-temporal data on U.S. unemployment rates. For this purpose, we present a family of models designed for the analysis and time-forward prediction of spatio-temporal econometric data. Our model is aimed at applications with spatially sparse but temporally rich data, i.e. for observations collected at few spatial regions, but at many regular time intervals. The family of models utilized does not make spatial stationarity assumptions and consists in a vector autoregressive (VAR) specification, where there are as many time series as spatial regions. A model building strategy is used that takes into account the spatial dependence structure of the data. Model building may be performed either by displaying sample partial correlation functions, or automatically with an information criterion. Monthly data on unemployment rates in the nine census divisions of the U.S. are analyzed. We show with a residual analysis that our autoregressive model captures the dependence structure of the data better than with univariate time series modeling.

This chapter introduces Learning Health Systems (LHS) and the impact of data science on such systems. It also examines the necessary properties of data used in LHS and identifies patients who may benefit from a transition to palliative care. Finally, it examines the way LHS can be used to identify racial and social disparities in access to palliative care.