Research on the influencing factors of customer referral behavior based on social network—Application in the catering industry

Shao, Jin-Yu; Zhang, Junhui; Guo, Beibei

doi:10.1016/j.hitech.2014.07.006

Cited by 7 publications

(11 citation statements)

References 23 publications

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“…It was chosen a case study with descriptive approach with quantitative and qualitative methodology [16], using a survey research that is more appropriate for this type of approach [08], [13] [14].…”

Section: Methodsmentioning

confidence: 99%

Relationships and Centrality in a Cluster of the Milk Production Network in the State of Parana/Brazil

Lima

Pona

Sacomano

et al. 2015

Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth

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The objective of this research is to evaluate the relationships of the network formed by the important milk cluster in the city of Umuarama, State of Parana (PR)/BRAZIL, using the Social Network Analysis (SNA) focusing on the collective gains and competitive advantages of this cluster. The methodology used was qualitative and quantitative. Questionnaires were applied to the network for the characterization of the existing relationships between them, and also to present the analysis of network measures using the UCINET software and the graphics schemes of networks. It was found that this milk production network appears to be diffuse, and that there are few solid relationships, which have no central coordination; the network did not present governance relationships nor a defined empowerment with significant transaction costs relationships. The relevance of this paper is to present a procedure of study in networks that can be reproduced in future researches.

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Section: Methodsmentioning

confidence: 99%

Relationships and Centrality in a Cluster of the Milk Production Network in the State of Parana/Brazil

Lima

Pona

Sacomano

et al. 2015

Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth

View full text Add to dashboard Cite

show abstract

“…(Vivek et al, 2012) In a wider scope, elements such as trust, loyalty, WOM, value and affective commitment appear in the theoretical model by Vivek et al (2012). Such elements are common ground in referral behaviour research and relationship marketing (Cetinā et al, 2014;Shi and Wojnicki, 2014;Sarathy and Patro, 2013;Shao et al, 2014;Schumann et al, 2010;Vivek et al, 2012;Yoo et al, 2015) thus the researchers expect these will play a role in educational RM also.…”

Section: Consumer Brand Engagementmentioning

confidence: 99%

“…In total, 100% of those interviewed either directly or indirectly mentioned rapport as a vital factor in RM. In other industries, relationship strength between consumer-consumer and consumer-organisation both have a positive impact on referral behaviour (Shao et al, 2014). Therefore, social networks are also a critical element of referral behaviour, as mentioned by employees repetitively.…”

Section: Rapport and Social Networkmentioning

confidence: 99%

Referral Marketing in Online Higher Education: a Holistic Snapshot of Strategic Initiatives, Effectiveness and Opportunities in a leading International Organization

Boros

Papasava

2020

JMCHE

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Referral Marketing (RM) has only recently sparked the interest of marketers in the online higher education (OE) sector, with distinct gaps identified in the literature. This concept is closely linked with consumer brand engagement, relationship marketing and student loyalty. The researchers selected a for-profit multinational OE organisation, which offers tertiary UK programmes and implements an incentivised RM strategy. Given that loyalty behaviour is linked with consumer experience, integrated marketing communications throughout the consumer journey are also believed to impact RM. The aim of this case study was to broaden knowledge and understanding of RM in this unique sector by identifying sectoral trends and investigating constructs of consumer brand engagement, employee engagement (EE) and integrated marketing communications through the lens of the OE sector. Through a mixed-methods design, combining elements of grounded theory and a constructivist paradigm, two discovery-oriented studies were conducted – namely qualitative interviews with 22 OE executives, and quantitative surveys with 100 OE students. Template analysis and quantitative statistics were implemented with an interpretive approach and methodological triangulation to ensure validity and reliability. Findings suggested a student-centred, bottom-up approach to IMC could be most successful, with employee ‘Belief in Strategy’ as a unique element of EE impacting on RM success.

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“…Yet, the prior online purchase experience is not relevant to the post-usage. And Shao et al (2014) studied that how customers' social network of the catering industry affects customers' referral behavior, and the result shows that network scale and structural holes do not influence customers' referrals.…”

Section: Catering Services and Tourismmentioning

confidence: 99%

The relative decision-making algorithm for ranking data

Chen

2020

DTA

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PurposeDecision-making is always an issue that managers have to deal with. Keenly observing to different preferences of the targets provides useful information for decision-makers who do not require too much information to make decisions. The main purpose is to avoid decision-makers in a dilemma because of too much or opaque information. Based on problem-oriented, this research aims to help decision-makers to develop a macro-vision strategy that fits the needs of different clusters of customers in terms of their favorite restaurants. This research also focuses on providing the rules to rank data sets for decision-makers to make choices for their favorite restaurant.Design/methodology/approachWhen the decision-makers need to rethink a new strategic planning, they have to think about whether they want to retain or rebuild their relationship with the old consumers or continue to care for new customers. Furthermore, many of the lecturers show that the relative concept will be more effective than the absolute one. Therefore, based on rough set theory, this research proposes an algorithm of related concepts and sends questionnaires to verify the efficiency of the algorithm.FindingsBy feeding the relative order of calculating the ranking rules, we find that it will be more efficient to deal with the faced problems.Originality/valueThe algorithm proposed in this research is applied to the ranking data of food. This research proves that the algorithm is practical and has the potential to reveal important patterns in the data set.

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Research on the influencing factors of customer referral behavior based on social network—Application in the catering industry

Cited by 7 publications

References 23 publications

Relationships and Centrality in a Cluster of the Milk Production Network in the State of Parana/Brazil

Relationships and Centrality in a Cluster of the Milk Production Network in the State of Parana/Brazil

Referral Marketing in Online Higher Education: a Holistic Snapshot of Strategic Initiatives, Effectiveness and Opportunities in a leading International Organization

The relative decision-making algorithm for ranking data

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