Social Listening Practices towards Social CRM and Customer Relationship Performance in the Fast-Food Industry in Sri Lanka

This study is carried out to identify the impact of social listening practices on social CRM and customer relationship performance in the fast-food industry in Sri Lanka. The target population for this study included the internal stakeholders from the organizations in the fast-food industry located in the Colombo metropolitan area which uses social media. The data was obtained via a structured questionnaire using a sample of 150 registered organizations. The time horizon was cross-sectional, and data were analyzed through both descriptive and inferential analysis. Based on the Resource-Based View (RBV) and the Capabilities Based Perspective, especially the dynamic capabilities theories, the conceptual model of this research study was developed by expecting that, organizations in the fast-food industry in Sri Lanka can exploit capabilities which are social listening practices and social CRM capabilities and resources which are customer relationship orientation and social media technology usage to obtain higher customer relationship performance.  Further, gain a competitive advantage over their competitors by effectively utilizing such resources. This is one of the few papers to exclusively focus on the impact of social listening practices on social CRM and customer relationship performance in the fast-food industry in Sri Lanka. The findings of this study have important implications for the fast-food industry in Sri Lanka. Keywords: Customer Relationship Management (CRM); Customer Relationship Orientation (CRO); Customer Relationship Performance; Social Customer Relationship Management (Social CRM) capabilities; Social media technology; Fast-food industr

Resilience models for New Zealand's alpine skiers based on people's knowledge and experience: a mixed method and multi-step fuzzy cognitive mapping approach

Artificial Neural Networks (ANN) as a tool offers opportunities for modeling the inherent complexity and uncertainty associated with socio-environmental systems. This study draws on New Zealand ski fields (multiple locations) as socio- environmental systems while considering their perceived resilience to low probability but potential high consequences catastrophic natural events (specifically earthquakes). We gathered data at several ski fields using a mixed methodology including: geomorphic assessment, qualitative interviews, and an adaptation of Ozesmi and Ozesmi’s (2003) multi-step fuzzy cognitive mapping (FCM) approach. The data gathered from FCM are qualitatively condensed, and aggregated to three different participant social groups. The social groups include ski fields users, ski industry workers, and ski field managers. Both quantitative and qualitative indices are used to analyze social cognitive maps to identify critical nodes for ANN simulations. The simulations experiment with auto-associative neural networks for developing adaptive preparation, response and recovery strategies. Moreover, simulations attempt to identify key priorities for preparation, response, and recovery for improving resilience to earthquakes in these complex and dynamic environments. The novel mixed methodology is presented as a means of linking physical and social sciences in high complexity, high uncertainty socio-environmental systems. Simulation results indicate that participants perceived that increases in Social Preparation Action, Social Preparation Resources, Social Response Action and Social Response Resources have a positive benefit in improving the resilience to earthquakes of ski fields’ stakeholders

The use of artificial neural networks to diagnose mastitis in dairy cattle

The use of milk sample categorization for diagnosing mastitis using Kohonen's self-organizing feature map (SOFM) is reported. Milk trait data of 14 weeks of milking from commercial dairy cows in New Zealand was used to train and test a SOFM network. The SOFM network was useful in discriminating data patterns into four separate mastitis categories. Several other artificial neural networks were tested to predict the missing data from the recorded milk traits. A multi-layer perceptron (MLP) network proved to be most accurate (R² = 0.84, r = 0.92) when compared to other MLP (R² = 0.83, r = 0.92), Elman (R² = 0.80, r = 0.92), Jordan (R² = 0.81, r = 0.92) or linear regression (R² = 0.72, r = 0.85) methods. It is concluded that the SOFM can be used as a decision tool for the dairy farmer to reduce the incidence of mastitis in the dairy herd

Green intraprenurial flexibility towards sustaining competitive advantage: A case of South Asian context

This study explores how green based intrapreneurial flexibility affects sustainable business performance of the Sri Lankan hotel industry. A survey was administered to a random sample of senior managers of hotels in Sri Lanka. Linear regression analysis revealed a significant path coefficient which explained green based intrapreneurial flexibility positively influenced sustainable competitive advantage. The findings suggest that hotel industry policy makers develop green specific intrapreneurial capabilities so that they can quickly adapt their green based product and service offerings in responding to changes of the green market requirements by focusing on green based new venture creation, green innovation, green related self-renewal exercises, and eco-friendly proactive decision making in order to sustain their competitive advantage from green initiatives

Impact of embedded AI mobile smart speech recognition on consumer attitudes towards AI and purchase intention across Generations X and Y

Purpose – This study aims to examine the influence of the derived attributes of embedded artificial intelligence-mobile smart speech recognition (AI-MSSR) technology, namely perceived usefulness, perceived ease of use (PEOU) and perceived enjoyment (PE) on consumer purchase intention (PI) through the chain relationships of attitudes to AI and consumer smart experience, with the moderating effect of consumer innovativeness and Generation (Gen) X and Gen Y in fashion retail. Design/methodology/approach – The study employed a quantitative survey strategy, drawing a sample of 836 respondents from Sri Lanka and India representing Gen X and Gen Y. The data analysis was carried out using smart partial least squares structural equation modelling (PLS-SEM). Findings – The findings show a positive relationship between the perceived attributes of MSSR and consumer PI via attitudes towards AI (AAI) and smart consumer experiences. In addition, consumer innovativeness and Generations X and Y have a moderating impact on the aforementioned relationship. The theoretical and managerial implications of the study are discussed with a note on the research limitations and further research directions. Practical implications – To multiply the effects of embedded AI-MSSR and consumer PI in fashion retail marketing, managers can develop strategies that strengthen the links between awareness, knowledge of the derived attributes of embedded AI-MSSR and PI by encouraging innovative consumers, especially Gen Y consumers, to engage with embedded AI-MSSR. Originality/value – This study advances the literature on embedded AI-MSSR and consumer PI in fashion retail marketing by providing an integrated view of the technology acceptance model (TAM), the diffusion of innovation (DOI) theory and the generational cohort perspective in predicting PI

スリランカにおける豆類遺伝資源の探索収集

Exploration mission for landraces of legumes was conducted in Sri Lanka in collaboration with the Plant Genetic Resource Centre of Sri Lanka from February 2 to March 2, 1995. This mission was part of a project funded by Japan International Cooperation Ahency (JICA). The mission explored the north-central dry zone, southern dry zone, upland intermediate zone and south-western wet zone of the country. A total of 146 seed samples which belong to 13 species of legume and 14 from other families were collected (Table 1). Most samples of legumes were Vigna unguiculata. Farmers distinguished two different types among the samples of this species, "yard long bean" of long round seeds and "cowpea" of angular seeds. They were called "m (e) a" and "cowpea", respectively. Immature pods of all these samples were used as vegetable. Samples of yard long bean varied in both seed coat color and pigmentation of immature pod. We could find kidney bean only in the areas at an altitude of more than 650m, while Vigna unguiculata samples were exclusive below 390m. From this observation, there seemed to be elevational differentiation in distribution of legumes for pod vegetables

Generation of Functional CLL-Specific Cord Blood CTL Using CD40-Ligated CLL APC

PMCID: PMC3526610This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited