Artificial intelligence (AI) conversational agents (CA) or chatbots represent one of the technologies that can provide automated customer service for companies, a trend encountered in recent years. Chatbot use is beneficial for companies when associated with positive customer experience. The purpose of this paper is to analyze the overall customer experience with customer service chatbots in order to identify the main influencing factors for customer experience with customer service chatbots and to identify the resulting dimensions of customer experience (such as perceptions/attitudes and feelings and also responses and behaviors). The analysis uses the systematic literature review (SLR) method and includes a sample of 40 publications that present empirical studies. The results illustrate that the main influencing factors of customer experience with chatbots are grouped in three categories: chatbot-related, customer-related, and context-related factors, where the chatbot-related factors are further categorized in: functional features of chatbots, system features of chatbots and anthropomorphic features of chatbots. The multitude of factors of customer experience result in either positive or negative perceptions/attitudes and feelings of customers. At the same time, customers respond by manifesting their intentions and/or their behaviors towards either the technology itself (chatbot usage continuation and acceptance of chatbot recommendations) or towards the company (buying and recommending products). According to empirical studies, the most influential factors when using chatbots for customer service are response relevance and problem resolution, which usually result in positive customer satisfaction, increased probability for chatbots usage continuation, product purchases, and product recommendations.

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Human-Computer Interaction in Customer Service: The Experience with AI Chatbots—A Systematic Literature Review

This research fills several gaps in the literature not investigated in previous studies. First, it examines how the responsible leadership (RL) of the chief executive officer (CEO) influences medium-sized technology farms to adopt environmental innovation (EI) through the pro-environmental behaviors (PBs) of the senior executive team (SET) according to the theory of social learning, as previous research only took institutional theory and utilitarianism as the driving factors of agricultural innovation. Second, we propose the potential growth model (PGM) from a sample of 105 CEOs and their SETs in medium-sized technology farms to handle the problem that an individual may regulate his behaviors based on how he translates and understands the surrounding environment, because previous research has ignored this perspective. Lastly, this research offers recommendations for the implementation of EI in medium-sized technology farms and also expands the related literature on sustainable agricultural production.

Why Do Medium-Sized Technology Farms Adopt Environmental Innovation? The Mediating Role of Pro-Environmental Behaviors

&lt;abstract&gt; &lt;p&gt;Text-based chatbots are implemented in the financial sector to enhance the relationship between the customer and services provided by the sector, and also to address external challenges and customer requirements. The chatbot technology in the financial sector serves to examine customers' frequently asked questions and the representation of the process using machine learning. In light of this, this study presents a comprehensive systematic literature review of articles focused on text-based chatbots in the financial sector. It describes the understanding of chatbots in the financial sector in terms of implementation, adoption intention, attitude toward use and acceptance; it also describes how people experience chatbots, specifically in terms of perception, expectation and trust, as well as how they are engaging and emotionally motivated; management of the security and privacy vulnerabilities of the chatbots; and identifies the potential strategies that can hinder the efficient, successful evolution of chatbots in the financial sector. Finally, the main findings regarding the use of text chatbots in the financial sector are presented; additionally, the open issues in current research are highlighted and a number of research opportunities that can be pursued in the future are suggested.&lt;/p&gt; &lt;/abstract&gt; 

Text-Based Chatbot in Financial Sector: A Systematic Literature Review

To achieve sustainable production in medium-sized farms, this research proposes a hierarchical linear modeling (HLM) to predict environmental strategy (ES), which is a crucial source of sustainable production. Based on the theory of upper echelons, the present research puts forward that the environmental leadership (EL) of the chief executive officer (CEO) at phase one affects the development of environmental corporate social responsibility (ECSR) adoption, which in turn affects the development of ES adoption over time. The empirical data were obtained through a three-stage sampling method of 90 CEOs and 270 members of senior management teams (SETs) of Taiwanese medium-sized farms, over a period of six months. The research results support that the higher level of CEO EL at phase one results in the development of ECSR adoption, which in turn results in the development of ES adoption. This research opens a new direction for sustainable production by showing how to implement ES through organizational management mechanisms (EL). These findings can fill the gaps in the literature on the sustainable production of farms and can also help these farms to achieve sustainable production by adopting ES.

How to Promote Medium-Sized Farms to Adopt Environmental Strategy to Achieve Sustainable Production during the COVID-19 Pandemic?

This survey employs the multilevel growth curve model to demonstrate how to promote the development of the company’s environmental innovation in agricultural companies specializing in the agricultural production and export of agricultural products to achieve sustainable production through environmental social responsibility and environmental engagement according to the engagement theory. The empirical data are collected 30 chief executive officers and their 90 supervisors of top management teams (TMTs) of Taiwanese agricultural companies in 2 months. The empirical results demonstrate that environmental social responsibility significantly influences the top management teams’ environmental engagement development, which in turn significantly influences the agricultural company’s environmental innovation. These empirical results can not only promote the sustainable production literature in the agricultural field but also help these agricultural companies implement environmental innovation to realize sustainable production of agricultural exports.

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How to Promote the Agricultural Company Through Environmental Social Responsibility to Achieve Sustainable Production?

To fill in the literature flaws that have not been detected in previous studies, this research, therefore, examines the driving factors of proactive environmental strategy (PES). First, this research proposes how corporate social responsibility (CSR) predicts the agricultural company’s PES through the intermediary mechanism of green organization identification (GOI) of the top management team (TMT) according to symbolic context and theory of high-level echelon, to solve the first gap in exploring what factors can drive the PES. Second, this research proposes a multi-level growth curve model (MGCM) to solve how individuals adjust their behavioral intentions over time according to their translation and understanding of their use environment, because past studies consist of almost cross-sectional properties. Third, past research has also neglected the multi-level framework, leading to hierarchical reasoning bias. Therefore, this research believes that the MGCM can fill in the multi-level gap. Finally, this research collected 400 TMT employees from 100 different agricultural companies in Taiwan in three-stage time for six months. The results show that CSR will significantly lead to more growth in GOI, and more growth in GOI will lead to more growth in PES adoption. The research results can not only advance the agricultural sustainability literature but also serve as a guide for agricultural companies to implement PES.

https://www.mdpi.com/2227-7390/9/16/1962/pdf

Constructing an Adoption Model of Proactive Environmental Strategy: A Novel Quantitative Method of the Multi-Level Growth Curve Model

The present research proposes the hierarchical linear modeling model (HLM) that describe how green social responsibility (GSR) predict the environmental strategy (ES) of agricultural technology manufacturing companies by the intermediary effects of the supervisor’s green promise (GP) based on symbolic context theory. This study collected data with 150 supervisors from 50 different agricultural technology companies in Taiwan to analyze the HLM. The results suggest that vendors of agricultural technology companies should establish GSR to increase GP, which consequently can increase the companies’ adoption of the ES. It is now the first to establish a milestone, propose a novel adoption model—GP and its antecedents through the HLM to predict the adoption of ES. These findings can upgrade the related literature of agriculture and can provide the procedure in implementing ES in agricultural technology companies.

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Why Can Green Social Responsibility Drive Agricultural Technology Manufacturing Company to Do Good Things? A Novel Adoption Model of Environmental Strategy

With the popularity of financial technology (fintech) chatbots equipped with artificial intelligence, understanding the user’s response mechanism can help bankers formulate precise marketing strategies, which is a crucial issue in the social science field. Nevertheless, the user’s response mechanism towards financial technology chatbots has been relatively under-investigated. To fill these literature gaps, latent growth curve modeling was adopted by the present research to survey Taiwanese users of fintech chatbots. The present study proposed a customer continuance model to predict continuance intention for fintech chatbots and that cognitive and emotional dimensions positively influence the growth in a user’s attitude toward fintech chatbots, which in turn, positively influences continuance intention over time. In total, 401 customers of fintech chatbots were surveyed through three time points to examine the relationship between these variables over six months. The results support the theoretical model of this research and can advance the literature of fintech chatbots and the information technology adoption model.

Shih-Chin Lee

Papers

Constructing an Adoption Model of Proactive Environmental Strategy: A Novel Quantitative Method of the Multi-Level Growth Curve Model

Why Can Green Social Responsibility Drive Agricultural Technology Manufacturing Company to Do Good Things? A Novel Adoption Model of Environmental Strategy

Toward a Unified Theory of Customer Continuance Model for Financial Technology Chatbots