THE EFFECT OF DISCOUNTS, ELECTRONIC WORD OF MOUTH (EWOM), AND PRICE TOWARDS INTEREST IN BUYING IN E-COMMERCE

The purpose of this study was to determine whether the Discounted Price, Electronic Word of Mouth, and Price affect the Purchase Interest of UIN Sunan Kalijaga Yogyakarta Students in Shopee E-Commerce. The population used is the students of UIN Sunan Kalijaga Yogyakarta. The number of samples in this study were 100 students of UIN Sunan Kallijaga Yogyakrata. This study uses primary data analysis method used is multiple linear regression analysis using SPSS version 23. The results of this study indicate that Discounted Price has a positive and significant effect on Purchasing Interest, Electrnic Word of Mouth has a positive and significant effect on Consumer Purchase Interest, Word of Mouth has a significant effect on Purchase Interest and Harag has a positive and significant effect on Buy Interest. Together, Discounts, Electronic Word of Mouth and Prices have a positive and significant effect on the Purchasing Interest of UIN Sunan Kaljaga Yogyakarta Students in E-Commerce Shopee. Companies should develop a Discount, Electronic Word of Mouth and Price strategy with the hope of increasing consumer Purchase Interest and can be used as a reference for the development and deepening of marketing management knowledge of FEBI UIN Sunan Kalijaga student

AN ANALYSIS OF TRANSACTIONS IN E-PAYMENT SYSTEM USING MOBILE AGENTS

Commercial interactions between merchants and customers pose a significant concern as they are associated with a large volume of data and complex information, especially when there is a need for switching requirements. This paper presents an agent-based analysis of e-payment transactions with the switching operations. The model adopts an inter-bank transaction network and consists of a terminal point of sale (POI) and three essential players in e-payment: customer, bank (merchant), and the Switch. This study analyses the various payment interactions using agent technology. The agent coordinates movement while the negotiation protocol serves as an internal control of the payment agreements, while the interactive hosts are the platforms that determine the status of transactions. Each agent host is equipped with a Certification Authority (CA) to secure communication between the merchant and the customer. Different transactions that agents could make are examined with formal descriptions. The implementation is achieved in Jade and compares with the object serialization mechanism. The simulation results show higher quality adaptation of agent systems and evidence of agentisation of e-transaction with Switch.     &nbsp

Artificial intelligence in business-to-business marketing: a bibliometric analysis of current research status, development and future directions

Purpose-Although the value of AI has been acknowledged by companies, the literature shows challenges concerning AI-enabled B2B marketing innovation, as well as the diversity of roles AI can play in this regard. Accordingly, this study investigates the approaches that AI can be used for enabling B2B marketing innovation. Design/methodology/approach-Applying a bibliometric research method, this study systematically investigates the literature regarding AI-enabled B2B marketing. It synthesises state-of-the-art knowledge from 221 journal articles published between 1990 and 2021. Findings-Apart from offering specific information regarding the most influential authors and most frequently cited articles, the study further categorises the use of AI for innovation in B2B marketing into five domains, identified the main trends in the literature, and suggest directions for future research. Practical implications-Through our identified five domains, practitioners can assess their current use of AI ability in terms of their conceptualisation capability, technological applications, and identify their future needs in the relevant domains in order to make appropriate decisions on whether to invest in AI. Thus, the research outcomes can help companies to realise their digital marketing innovation strategy through AI. Originality/value-While more and more studies acknowledge the potential value of AI in B2B marketing, few attempts have been made to synthesise the literature. The results from the study can contribute by 1) obtaining and comparing the most influential works based on a series of analyses; 2) identifying five domains of research into how AI can be used for facilitating B2B marketing innovation; and 3) classifying relevant articles into five different time periods in order to identify both past trends and future directions in this specific field

INOVAÇÃO NOS CANAIS DE COMUNICAÇÃO COMO FORMA DE COMERCIALIZAÇÃO

A constante mudança tecnológica impõe ás industrias novos desafios e necessidades de adaptações, a maneira de se relacionar com os clientes se renova frequentemente com o desenvolvimento de novos canais de comunicação. Esse artigo fará uma abordagem prática sobre a efetividade dos canais de comunicação: Google AdWords, e-mail marketing e Facebook integrados com o e-commerce no aspecto de prospecção de clientes. Em sequência avalia-se o comportamento da conversão dos clientes prospectados em venda efetivamente. Foram utilizados dados de 27 meses de campanha de marketing de uma indústria metalúrgica em cada um dos 3 canais de comunicação. Posteriormente foi feito a análise do índice de correlação de Cohen e inferido análises de regressão linear e one-way ANOVA que explicassem estatisticamente a dinâmica das campanhas de marketing nos diferentes canais de comunicação com a atração de clientes. Comprovadamente, conclui-se que as campanhas de marketing possuem efeito positivo no

Development of a Cross-border Business-to-Business-to-Consumer (B2B2C) System to Enhance Enterprise Performance: A Case Study of Legend Harvest Group

This research focused on the efforts of Legend Harvest Group (LHG), a California startup, to realise its cross-border business-to-business-to-consumer (B2B2C) e-commerce business opportunities. The issues identified during the research demonstrated that an operational B2B2C system is more complicated than a manually operated business-to-business (B2B) trade. The complexities of cross-border e-commerce platforms include insufficient data transparency, logistical obstacles, and Customs hurdles. LHG encountered difficulties in understanding and dealing with these obstacles. My research focused on analysing the technological, operational and organisational requirements and finding the critical elements and leverage points of adopting a new B2B2C system. I developed a platform–system–technology–human (PSTH) conceptual framework based on my literature review that served as the theoretical blueprint of this action research. I adopted a participatory action research (PAR) method and a purposeful sampling strategy to conduct an action research study. The sampling population comprised LHG’s executives, as well as board members, officers, employees, and consultants associated with the company. I applied a qualitative approach as the most suitable choice in action research study, using interviews, semi-structured discussions, and observations to collect data. This research was based on three action cycles. Each action cycle consisted of four phases: reflect, plan, act and observe. The first action cycle (AC1) focused on scanning the environment to identify the barriers preventing LHG from adopting a B2B2C system. The second action cycle (AC2) addressed the technological, operational and organisational requirements, and collaborated with a Software-as-a-Service (SaaS) provider to implement a trial run and collect actual data. The third action cycle (AC3) involved an in-depth thematic analysis to evaluate the trial-run results and proposed an integrators network for LHG’s future B2B2C system development. Research accomplishments include initial identification of sixty-one emergent codes as barriers to LHG’s supply chain automation quest, categorisation of these codes into fifteen actionable themes, and, finally, selection of five actionable themes as critical elements to follow in adopting a B2B2C system, namely, process automation (A), SaaS adoption (S), supply chain integration (I), collaboration (C) and trust (T). From post-trial-run analysis, I recognised these five themes as the key integrators and proposed a B2B2C supply chain model to cope with the cross-border e-commerce platforms. The interdependent nature of these five integrators led to the conceptualisation of an “ASICT” network that can be used to tackle the platforms’ demands. Based on the research findings, I learned that a sustainable B2B2C system will depend not only on technology implementation such as SaaS adoption, supply chain integration and process automation, but also on human interaction such as collaboration and trust. This research concluded that these five “ASICT” integrators are critical elements, and that trust and collaboration are the key leverage points in the company’s efforts to develop a cross-border B2B2C system. The benefits projected by adopting the B2B2C system included not only reducing LHG’s transactional costs but also enhancing its enterprise performance by automating and integrating the supply chain, allowing the management to map operational efficiency with financial outcome and to transform the e-commerce supply chain into a value chain

Socio-technical transitions in the logistics sector: how companies manage their innovation in the era of digitalisation

There is a growing theoretical interest in the role of firms in socio-technical transitions studies. In doing so, transitions scholars start to explore business model innovation in the context of sustainability transitions. However, due to a lack of a firm-level perspective in transitions theory, it is still unclear how business model innovation unfolds in a socio-technical system context over time. This thesis adopts an S-D logic, service ecosystems view on the role of firms to extend the transitions theory. Besides, logistics innovations have not been widely explored in the transitions literature. As one of the first studies to explore logistics innovations from a socio-technical transitions perspective, this thesis also contributes to understanding the system reconfiguration of production and consumption systems from a logistics perspective. This thesis employs a multiple-case studies design to investigate firms’ innovation activities and their impact at the micro-, meso-, and macro-levels of service ecosystems. Qualitative research methods have been used to investigate firms’ innovation projects. The thesis then examines the interrelation between innovation activities, logistics strategies, and logistics trends to explain not only why firms have to balance their innovation efforts at the micro-level of the service ecosystem, but also how logistics innovations unfold at the meso- and meso-levels by the enactment of these value propositions. In light of the investigation, this thesis adopts a balanced view of the relationship between firms and socio-technical systems, which helps overcome the ‘niche-actor’ and ‘regime-actor’ dichotomy in transitions studies. Also, this thesis provides a conceptual framework that bridges production and consumption by using logistics innovations as an empirical lens. Finally, due to the exploratory nature of this thesis, these findings may provide valuable insights for future research that integrate these two research streams for a better understanding of the firm-level innovation activities in socio-technical transitions

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Essays on Predictive Analytics in E-Commerce

Die Motivation für diese Dissertation ist dualer Natur: Einerseits ist die Dissertation methodologisch orientiert und entwickelt neue statistische Ansätze und Algorithmen für maschinelles Lernen. Gleichzeitig ist sie praktisch orientiert und fokussiert sich auf den konkreten Anwendungsfall von Produktretouren im Onlinehandel. Die “data explosion”, veursacht durch die Tatsache, dass die Kosten für das Speichern und Prozessieren großer Datenmengen signifikant gesunken sind (Bhimani and Willcocks, 2014), und die neuen Technologien, die daraus resultieren, stellen die größte Diskontinuität für die betriebliche Praxis und betriebswirtschaftliche Forschung seit Entwicklung des Internets dar (Agarwal and Dhar, 2014). Insbesondere die Business Intelligence (BI) wurde als wichtiges Forschungsthema für Praktiker und Akademiker im Bereich der Wirtschaftsinformatik (WI) identifiziert (Chen et al., 2012). Maschinelles Lernen wurde erfolgreich auf eine Reihe von BI-Problemen angewandt, wie zum Beispiel Absatzprognose (Choi et al., 2014; Sun et al., 2008), Prognose von Windstromerzeugung (Wan et al., 2014), Prognose des Krankheitsverlaufs von Patienten eines Krankenhauses (Liu et al., 2015), Identifikation von Betrug Abbasi et al., 2012) oder Recommender-Systeme (Sahoo et al., 2012). Allerdings gibt es nur wenig Forschung, die sich mit Fragestellungen um maschinelles Lernen mit spezifischen Bezug zu BI befasst: Obwohl existierende Algorithmen teilweise modifiziert werden, um sie auf ein bestimmtes Problem anzupassen (Abbasi et al., 2010; Sahoo et al., 2012), beschränkt sich die WI-Forschung im Allgemeinen darauf, existierende Algorithmen, die für andere Fragestellungen als BI entwickelt wurden, auf BI-Fragestellungen anzuwenden (Abbasi et al., 2010; Sahoo et al., 2012). Das erste wichtige Ziel dieser Dissertation besteht darin, einen Beitrag dazu zu leisten, diese Lücke zu schließen. Diese Dissertation fokussiert sich auf das wichtige BI-Problem von Produktretouren im Onlinehandel für eine Illustration und praktische Anwendung der vorgeschlagenen Konzepte. Viele Onlinehändler sind nicht profitabel (Rigby, 2014) und Produktretouren sind eine wichtige Ursache für dieses Problem (Grewal et al., 2004). Neben Kostenaspekten sind Produktretouren aus ökologischer Sicht problematisch. In der Logistikforschung ist es weitestgehend Konsens, dass die “letzte Meile” der Zulieferkette, nämlich dann wenn das Produkt an die Haustür des Kunden geliefert wird, am CO2-intensivsten ist (Browne et al., 2008; Halldórsson et al., 2010; Song et al., 2009). Werden Produkte retourniert, wird dieser energieintensive Schritt wiederholt, wodurch sich die Nachhaltigkeit und Umweltfreundlichkeit des Geschäftsmodells von Onlinehändlern relativ zum klassischen Vertrieb reduziert. Allerdings können Onlinehändler Produktretouren nicht einfach verbieten, da sie einen wichtigen Teil ihres Geschäftsmodells darstellen: So hat die Möglichkeit, Produkte zu retournieren positive Auswirkungen auf Kundenzufriedenheit (Cassill, 1998), Kaufverhalten (Wood, 2001), künftiges Kaufverhalten (Petersen and Kumar, 2009) und emotianale Reaktionen der Kunden (Suwelack et al., 2011). Ein vielversprechender Ansatz besteht darin, sich auf impulsives und kompulsives (LaRose, 2001) sowie betrügerisches Kaufverhalten zu fokussieren (Speights and Hilinski, 2005; Wachter et al., 2012). In gegenwärtigen akademschen Literatur zu dem Thema gibt es keine solchen Strategien. Die meisten Strategien unterscheiden nicht zwischen gewollten und ungewollten Retouren (Walsh et al., 2014). Das zweite Ziel dieser Dissertation besteht daher darin, die Basis für eine Strategie von Prognose und Intervention zu entwickeln, mit welcher Konsumverhalten mit hoher Retourenwahrscheinlichkeit im Vorfeld erkannt und rechtzeitig interveniert werden kann. In dieser Dissertation werden mehrere Prognosemodelle entwickelt, auf Basis welcher demonstriert wird, dass die Strategie, unter der Annahme moderat effektiver Interventionsstrategien, erhebliche Kosteneinsparungen mit sich bringt