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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.

The purpose of this paper is to advance the understanding of brand love by studying its intensity and the nature of extreme forms of it, rather than its presence or absence. The love of a sports team is a type of brand love and is a valuable context to study of brand love intensity because the intensity of love can become more extreme than for products; it has two distinctive features that are theoretically, management and policy relevant; and it is an under-researched context in marketing that is socially and economically significant.

The authors empirically develop and test a multidimensional hierarchical higher-order measure of the intensity of team love and a model of its drivers and outcomes using a sample of supporter club members of a professional sports team who vary in their intensity of love for the team.

The results support our measurement model and its distinctive features, especially the importance of the perceived two-way bond fans have with their team. While overall intensity of team love is not related to social influence or on-field performance, as hypothesized, they are related to sub-dimensions of team love, reflecting its multidimensionality. As hypothesized, the intensity of team love and social influence are related to the intention to renew club membership even with increased costs and poor performance and social influence is directly related to word of mouth and game attendance.

The research is limited to the club members of one sports team in a particular sport in one country and one cultural context. Future research opportunities include: extending it to other sports and brand contexts, refining the methodology and addressing other issues highlighted by the research.

The results indicate the limits of management control of team love intensity because it develops over time independently through social processes. However, firms can help facilitate these processes. The social dimensions indicate the need to develop socially, as well as individually-focussed relationship management strategies. Most devoted fans are valuable customers, but some hardcore elements can be dysfunctional and sabotage the brand.

Sport is personally, social and economically significant in most cultures and love of a sports team love can be an important glue that binds people and communities. However, the existence of extreme hardcore fans and heated rivalries can also be divisive and pose challenges for social policy. Hence, the need to better understand the factors driving more extreme forms of team love to better inform the development of social policy.

The authors focus on the intensity of brand love rather than its presence and absence as in prior research. The authors develop and test a new hierarchical measure of sports team love intensity and a model of its drivers and outcomes. The sports context is under-researched in marketing but reveals the important role played by dimensions that are obscured in studies of product brand love – its social nature and the perceived reciprocal relation with devoted fans. The results contribute to developing extended theories of brand love, open up new research opportunities and have management and policy implications.

This paper aims to develop a novel and generalizable machine-learning based method of measuring established marketing constructs through passive analysis of consumer-generated textual data. The authors term this method scale-directed text analysis.

The method first develops a dictionary of words related to specific dimensions of a construct that is used to assess textual data from any source for a specific meaning. The method explicitly recognizes both specific words and the strength of their underlying sentiment.

Results calculated using this new approach are statistically equivalent to responses to traditional marketing scale items. These results demonstrate the validity of the authors’ methodology and show its potential to complement traditional survey approaches to assessing marketing constructs.

The method we outline relies on machine learning and thus requires either large volumes of text or a large number of cases. Results are reliable only at the aggregate level.

The method detail provides a means of less intrusive data collection such as through scraped social media postings. Alternatively, it also provides a means of analyzing data collected through more naturalistic methods such as open-response forms or even spoken language, both likely to increase response rates.

Scale-directed text analysis goes beyond traditional methods of conducting simple sentiment analysis and word frequency or percentage counts. It combines the richness of traditional textual and sentiment analysis with the theoretical structure and analytical rigor provided by traditional marketing scales, all in an automatic process.

The purpose of this paper is to examine how movie studios develop an integrated social media strategy to achieve box office success. Departing from prior studies which focus on single social media platforms, this study examines the role of integrated social media promotion strategy using multiple social media platforms on movie success in the Bollywood movie industry.

This study adopts an in-depth and comprehensive case study approach to examine the promotional strategies adopted through YouTube, Facebook and Twitter throughout the life cycle of the movie and its impact on the box office success of the movie.

The study provides three major findings. First, the social media promotional strategy was centred on developing appropriate content to match the unique characteristics of the social media platforms. While Facebook was utilised primarily to connect audiences through organising fun events, Twitter was used to retweet the positive word-of-mouth generated from the audiences. Second, emphasis on promotional strategy through social media platforms in the post-release stage of the movie was found to be equally important as the pre-release stage. Finally, the social media platforms were utilised to develop emotional connection with the audience by promoting the content through which the audience identified themselves with the main protagonist of the movie.

This study is among the very few studies which examines the role of integrative social media strategy on the box office success in the movie industry. This study emphasises the way firms can utilise the synergies across different social media platforms to achieve success in the movie industry.

The purpose of this paper is to examine the impact of the Sydney 2000 Olympic Games on the residential real estate markets of the host city during the bidding, pre-Olympic and post-Olympic periods.

This study uses a difference-in-differences model to analyze the transaction prices for all properties in New South Wales, Australia for the period from 1980 to 2007.

The paper finds that the impact on real estate markets varies across different suburbs in the host city and over time. The real estate markets of host suburbs experience substantially higher growth during the bidding and pre-Olympic periods but not during the post-Olympic period. However, the property prices in non-host suburbs in the host city increase at a higher rate during the pre- and post-Olympic periods but not during the bidding period.

This study offers insights into the long-term impact of the Olympic Games on host suburbs and non-host suburbs in the host city during different periods by analyzing a large longitudinal data set over a period of 27 years.

The purpose of this paper is to study the spillover effects of marketing expertise on the market performance of domestic firms and multinational enterprises (MNEs). Specifically, this study examines how the adoption of frequency loyalty programs by a domestic firm following an MNE affects the competitive dynamics and the market performance of both firms in a Chinese retail gasoline market.

This study is based on empirical data that were obtained from a quasi-field experiment in which the MNE entered the market with a frequency loyalty program and the domestic firm later responded with a similar loyalty program. The authors measured the impact of the adoption of a frequency loyalty program by the domestic firm on the market performance of both the domestic firm and the MNE.

The authors find that the domestic firm’s adoption of a similar loyalty program significantly increased its market share in the regular gasoline market. The domestic firm’s adoption of a loyalty program also increased the market performance of the MNE in the premium gasoline market.

This study explicitly demonstrates the spillover benefits through demonstration effects and provides empirical evidence on specific spillover benefits to domestic firms and MNEs based on their competencies in distinct market segments where they compete.

This study empirically investigates how ambidextrous innovations and their balancing affect the supply chain financing performance (SCFP) of small and medium-sized enterprises (SMEs), based on signaling theory. Moreover, this study explores the moderating effect of the breadth and depth of digital technology deployment on the relationship between ambidextrous innovations and the SCFP of SMEs.

A mixed-methods design is used, including a qualitative study and a quantitative study. Qualitative data have been collected from six multi-cases in different industries. Questionnaire data have been collected from 259 SMEs in China, and a multiple regression model is used to verify the research hypotheses.

The findings indicate that, in supply chain financing, both exploitative innovation and exploratory innovation are helpful in improving the SCFP of SMEs. For resource-constrained SMEs, a relative balance between exploitative innovation and exploratory innovation can help improve SCFP. The breadth of digital technology deployment can strengthen the relationship between exploitative innovation and SCFP, while the depth of digital technology deployment can weaken the relationship between exploratory innovation and SCFP. In addition, increasing the depth of digital technology deployment strengthens the positive correlation between the relative balance of ambidextrous innovations and SCFP.

To effectively obtain supply chain financing, SMEs can either concentrate their limited resources on a single type of innovation or use relative balance strategies to simultaneously pursue two innovations. In addition, in the process of obtaining supply chain financing by ambidextrous innovations, SMEs should appropriately deploy digital technologies.

This study first deconstructs the impact mechanism of ambidextrous innovation capabilities on SCFP based on signaling theory, and then discusses the balancing effect of ambidextrous innovations on SCFP in the cases of resource-constrained SMEs. This study also goes further and finds the negative moderating effect of digital technology deployment in the process of supply chain financing.

This paper aims to explore how innovation capability and market response capability of small and medium-size enterprises (SMEs) affect their supply chain financing performance (SCFP) through supply chain financing solutions (SCFS) adoption. At the same time, the mechanism by which supply chain financing reduces information asymmetry before (ex-ante) and after (ex-post) SCFS adoption to promote SCFP is also inquired.

Drawing on enterprise competence theory, this paper proposes a theoretical model and tests it using survey data from a sample of 218 SMEs in China. Multiple regression analysis is employed to test the hypothesis.

The study finds that: (1) SMEs' innovation capability and market response capability positively affect SCFP. (2) SMEs' innovation capability and market response capability exert significantly positive effects on SCFS adoption. (3) SCFS adoption plays a mediating role between SME capabilities and SCFP. (4) Supply chain integration (SCI) and information technology application have no moderating effects on the relationship between SME capabilities and SCFS adoption. Finally, (5) SCI and information technology application have positive moderating effects on the relationship between SCFS adoption and SCFP.

Based on enterprise competence theory, this study sheds light on the internal mechanism through which SMEs' capabilities affect SCFP by introducing SCFS adoption and explores the role of situational factors in SCF in reducing ex-ante and ex-post information asymmetry. This study provides an innovative theoretical perspective on supply chain financing and enriches the existing research.

Historical newspaper collections provide a wealth of information about the past. Although the digitization of these collections significantly improves their accessibility, a large portion of digitized historical newspaper collections, such as those of KBR, the Royal Library of Belgium, are not yet searchable at article-level. However, recent developments in AI-based research methods, such as document layout analysis, have the potential for further enriching the metadata to improve the searchability of these historical newspaper collections. This paper aims to discuss the aforementioned issue.

In this paper, the authors explore how existing computer vision and machine learning approaches can be used to improve access to digitized historical newspapers. To do this, the authors propose a workflow, using computer vision and machine learning approaches to (1) provide article-level access to digitized historical newspaper collections using document layout analysis, (2) extract specific types of articles (e.g. feuilletons – literary supplements from Le Peuple from 1938), (3) conduct image similarity analysis using (un)supervised classification methods and (4) perform named entity recognition (NER) to link the extracted information to open data.

The results show that the proposed workflow improves the accessibility and searchability of digitized historical newspapers, and also contributes to the building of corpora for digital humanities research. The AI-based methods enable automatic extraction of feuilletons, clustering of similar images and dynamic linking of related articles.

The proposed workflow enables automatic extraction of articles, including detection of a specific type of article, such as a feuilleton or literary supplement. This is particularly valuable for humanities researchers as it improves the searchability of these collections and enables corpora to be built around specific themes. Article-level access to, and improved searchability of, KBR's digitized newspapers are demonstrated through the online tool (https://tw06v072.ugent.be/kbr/).