84 research outputs found
Supplemental Material, Exec_summary - Too Good to Be True? Boundary Conditions to the Use of Downward Social Comparisons in Service Recovery
No full textSupplemental Material, Exec_summary for Too Good to Be True? Boundary Conditions to the Use of Downward Social Comparisons in Service Recovery by Paolo Antonetti, Benedetta Crisafulli, and Stan Maklan in Journal of Service Research</p
Towards a Better Measure of Customer Experience
No full textDefining and improving customer experience is a growing priority for market research because experience is replacing quality as the competitive battleground for marketing. Service quality, we argue, is an outgrowth of the Total Quality Management movement of the 1980s and suffers from that movement’s focus on the provider rather than the value derived by customers. The most popular measure of service quality – SERVQUAL – assesses the functional delivery of service during a single episode. This conceptualisation allows service to be improved along traditional quality management principles. The increasingly settled view of researchers is that customer experience is generated through a longer process of company-customer interaction across multiple channels and is generated through both functional and emotional clues. Research with practitioners indicates that most firms use customer satisfaction, or its derivative Net Promoter Score, to assess their customers’ experiences. We question this practice based on the conceptual gap between these measures and the customer experience. In the IJMR October 2011, we proposed the principles of a new measure appropriate for the modern conceptualisation of customer experience: the Customer Experience Quality (EXQ) scale. In this article we extend that work to four service contexts to support a claim of generalisability better and compare its predictive power with that of customer satisfaction. We propose that EXQ better explains behavioural intention and recommendation than customer satisfaction
Re-examining dynamic capabilities in the context of digital transformation.
No full textMaklan, Stan - Associate SupervisorWhile digital transformation is often a necessity to allow incumbent firms to
remain competitive in a fast-changing world, it suffers from high failure rates in
practice. The dynamic capability perspective was developed to address rapidly
changing environments, so it can be utilised as a theoretical foundation to
improve our understanding of digital transformation. With dynamic capabilities
often disaggregated into three capability clusters: sensing, seizing, and
transforming, these clusters are mostly presented in a static sequence and evolve
independently, which is a practice challenged by this thesis.
To explore the possible reasons hindering digital transformation, a
longitudinal case study is conducted, exploring the evolution of dynamic
capability clusters over time. It is observed that sensing, seizing, and transforming,
rather than being sequential, coexist and coevolve during digital transformation.
When they evolve at different speeds, mismatches can occur, which can act as
bottlenecks slowing down the transformation but at the same time can act as
catalysts improving underdeveloped capabilities. This finding contributes to the
theory by demonstrating how mismatches arise during the coevolution of dynamic
capability clusters and discussing their consequences for digital transformation.
This finding also contributes to practice by arguing that the way in which firms
orchestrate the coevolution of these dynamic capabilities over time holds a key
to successful digital transformation, providing a more dynamic approach for
emergent strategy development. It is therefore suggested that managers
embrace the tensions caused by these mismatches and adopt a mindset that
allows them to concurrently improve different dynamic capability clusters
supporting digital transformation.
While dynamic capabilities were introduced to address the static nature of
the resource-based view (RBV), as previously described, the sensing, seizing,
and transforming clusters are often applied in a sequential fashion, ignoring their
possible interdependencies and evolutionary paths, and thus failing to capture
the essential dynamism of the underlying phenomenon, which is particularly
important in a high-velocity digital context. Therefore, this study further developed
the conceptualisation of dynamic capability from an evolutionary perspective,
better serving the current digital environment, which is changing faster than ever.
As regards future research, firstly, since this thesis advances the
conceptualisation of sensing, seizing, and transforming capabilities from an
evolutionary perspective, it needs to be validated by more empirical studies.
Secondly, the context is a limitation of this thesis. While this thesis provides deep
insights through a single longitudinal case study in the retail sector, more studies
are called for in diverse industries and national contexts to examine the
coevolution of dynamic capabilities over time. Thirdly, while this thesis observes
the mismatches during the coevolution of dynamic capabilities, further research
is needed to explore the fundamental reasons behind this observation. The
potential reasoning assumptions proposed by this thesis in attempting to explain
the fundamental mechanism of dynamic capability mismatches require further
examination via empirical research. Fourthly, an evolutionary underpinning
indicates the methodological implications, calling for a longitudinal research
design that moves away from a serial view in order to further advance and
validate the framework of sensing, seizing, and transforming.PhD in Leadership and Managemen
Corporate social responsibility programmes and their impact on business decision making
No full textBased upon an empirical study of CSR programmes across a number of multinational
companies, we explore some of the underlying reasons why CSR seems to have a low
impact on business decision-making through a validated framework linking CSR
programmes with business and social outcomes
Customer Relationship Management: Concepts and Technologies
No full textThis much-anticipated new edition of the bestseller Customer Relationship Management: Concepts and Technologies provides a comprehensive and balanced review of CRM, now completely revised to reflect recent changes in CRM practice. The book explains what CRM is, the benefits it delivers, the contexts in which it is used, the technologies that are deployed, and how it can be implemented.
Both theoretically sound and managerially relevant, the book draws on academic and independent research from a wide range of disciplines including IS, HR, project management, finance, strategy and more. Buttle and Maklan, clearly and without jargon, explain how CRM is used throughout the customer life cycle stages of customer acquisition, retention and development. The book is illustrated liberally with screenshots from CRM software applications and case illustrations of CRM in practice.
NEW TO THIS EDITION:
Updated instructor support materials online
Full colour interior
Brand new international case illustrations from many industry settings
Substantial revisions throughout, including new content on:
o Social media and social CRM
o Big data and unstructured data
o Recent advances in analytical CRM including next best action solutions
o Marketing, sales and service automation
o Customer self-service technologies
o Making the business case and realising the benefits of investment in CRM
Ideal as a core textbook for students on CRM or related courses such as relationship marketing, database marketing or key account management, the book is equally valuable to industry professionals, managers involved in CRM programs and those pursuing professional qualifications or accreditation in marketing, sales or service management
A systematic review of measurements of service quality and consumer experience
No full textThe challenge of predicting consumer behaviour is widely considered by the literature as a
rather daunting, but worthwhile task. Which manager or academic would not be interested in
using or developing a framework enabling one to predict future behaviour better than existing
measurements? Refering to the old saying, stating that ‘only what gets measured, gets managed’,
indicating what the literature addresses as a need to track the influence of change through
measurements. In order to address my research question and explore the proposition ‘Can a
measurement of service quality based on consumer experience be a better predictor of consumer
behaviour?’ this paper examines the existing literature in two fields of literature. On the one
hand I will be investigating studies in the context of existing measurements of service quality to
assess the first part of my research question to determine the ‘status quo’, application and
characteristics of the literature on measurements of service quality. On the other hand the paper
will select, appraise, and synthesize the relevant literature on consumer behaviour to address the
second part of the research question, if, and if yes, how the phenomenon of consumer experience
could be the foundation for a measurement of service quality capable of predicting consumer
behaviour better than existing measurements of service quality.
By systematically reviewing the existing literature I am aiming on contributing to the literature
addressing the challenges of predicting consumer behaviour
EXQ: development and validation of a multiple-item scale for assessing customer experience quality
No full textPositioned in the deliberations related to service marketing, the conceptualisation of service
quality, current service quality measurements, and the importance of the evolving construct of
customer experience, this thesis develops and validates a measurement for customer experience
quality (EXQ) in the context of repeat purchases of mortgage buyers in the United Kingdom.
The thesis explores the relationship between the customer experience quality and the important
marketing outcomes of customer satisfaction, repeat purchasing behaviour, loyalty and word-of-
mouth intentions.
The methodology follows Churchill’s (1979) scale development paradigm approach to scale
development and is also informed by the more recent publication of Walsh and Beatty (2007).
This involves creating the EXQ scale from the following sequence of research activities: (a)
employing a review of the literature on service marketing, service quality, service quality
measurements, and customer experience research; (b) generating an initial item pool from
qualitative research; (c) purifying and validating the EXQ scale through exploratory factor
analysis (EFA), confirmatory factor analysis (CFA), and structural equation modelling (SEM).
The EXQ scale explains 63 per cent of all variances in customer satisfaction, more than 86 per
cent of loyalty, and more than 94 per cent of word-of-mouth intentions. This is evidence of the
high explanatory power of the EXQ scale for important marketing outcomes. This thesis
represents both the first empirically derived conceptualisation of customer experience and the
first validated measure of customer experience quality. It reports the findings collected from three
independent samples of repeat mortgage buyers from a United Kingdom bank
Dynamic capabilities: the missing link in CRM investments
No full textThe purpose of this paper is to illustrate the practical application of dynamic
capabilities theory to improve investment decisions in customer relationship
management (CRM). Design/methodology/approach – Action research (AR) allows
managers to raise the tacit knowledge of their dynamic capabilities to a level
where they can be identified and developed. A framework and a process for
managing dynamic capabilities in marketing are presented. Findings – The
findings relate to the nature of dynamic capabilities in marketing and how they
are managed. Practical implications – Marketing managers can improve the return
on investments in CRM. Originality/value – The paper presents a method for
applying dynamic capabilities drawn from the resource-based view (RBV) to
practical marketing
Improving the direct marketing practices of FMCG retailers through better customer selection. An empirical study comparing the effectiveness of RFM (Recency, Freuency and Monetary) CHAID (Chi-squared Automatic Interaction Detection), stepwise logit (logistic regression) and ANN (Artificial Neural Networks) techniques using different data variable depths
No full textThe intent of this thesis is to understand Data Mining technique effectiveness in both shallow (RFM variable only) and expanded data environments. The thesis addresses two specific gaps in research: (1) the relationship between customer selection techniques and performance and (2) the effects of using different depths of data on performance. In shallow-data contexts stepwise logit and neural networks provided the greatest cumulative lift and outperformed both RFM and CHAID across all top deciles. However, RFM shows the second highest fit measure, illustrating its relative stability in predicting outcomes. In addition, the RFM technique performance was tested using both one-month and 12-month time series. The 12-month series performed better and showed a greater level of fit. The subsequent study comparing technique effectiveness under expanded variable sets demonstrated an even more significant and visible lift increase versus the RFM technique. Looking at logistic regression, CHAID and neural networks, the lifts and gains obtained at the first two deciles provide enough response lift to allow these techniques’ cumulative performance to surpass RFM well past decile five into decile six. From a cumulative perspective, the strong performance of logit and ANN allow these techniques to outperform CHAID in deciles one and two, but as of decile three, cumulative performance of all three advanced techniques becomes virtually identical. Though CHAID remains the technique with the best fit performance, RFM fit value falls to last place once an expanded variable set is introduced. Furthermore, both logistic and ANN performance increases significantly, and though they remain very close from an overall Gini and PCC score perspective, the logistic regression outperforms ANN when using expanded data. In both studies, dimensionality reduction plays a role in optimising model response. In limited data sets, logit applications reduced data to achieve better response, whereas in extended data sets, all models applied reductions. These findings contribute to the growing literature on customer selection techniques and provide a specific contribution to data mining, RM, segmentation and marketing practice by demonstrating how these techniques can be used for better consumer selection for purposes of customer development in FMCG retail
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