Artificial intelligence in agricultural value chain: review and future directions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
C. Ganeshkumar ◽  
Sanjay Kumar Jena ◽  
A. Sivakumar ◽  
T. Nambirajan
Keyword(s):  
Artificial Intelligence ◽  
Value Chain ◽  
Water Resource Management ◽  
Learning Algorithm ◽  
Demand Forecasting ◽  
Future Research ◽  
Content Type ◽  
Deep Learning Algorithm ◽  
Price Demand ◽  
Pesticide Usage

PurposeThis paper is a literature review on use of artificial intelligence (AI) among agricultural value chain (AVC) actors, and it brings out gaps in research in this area and provides directions for future research.Design/methodology/approachThe authors systematically collected literature from several databases covering 25 years (1994–2020). They classified literature based on AVC actors present in different stages of AVC. The literature was analysed using Nvivo 12 (qualitative software) for descriptive and content analysis.FindingsFifty percent of the reviewed studies were empirical, and 35% were conceptual. The review showed that AI adoption in AVC could increase agriculture income, enhance competitiveness and reduce cost. Among the AVC stages, AI research related to agricultural processing and consumer sector was very low compared to input, production and quality testing. Most AVC actors widely used deep learning algorithm of artificial neural networks in various aspects such as water resource management, yield prediction, price/demand forecasting, energy efficiency, optimalization of fertilizer/pesticide usage, crop planning, personalized advisement and predicting consumer behaviour.Research limitations/implicationsThe authors have considered only AI in the AVC, AI use in any other sector and not related to value chain actors were not included in the study.Originality/valueEarlier studies focussed on AI use in specific areas and actors in the AVC such as inputs, farming, processing, distribution and so on. There were no studies focussed on the entire AVC and the use of AI. This review has filled that literature gap.

Artificial intelligence in financial services: a qualitative research to discover robo-advisory services

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ankita Bhatia ◽  
Arti Chandani ◽  
Rizwana Atiq ◽  
Mita Mehta ◽  
Rajiv Divekar
Keyword(s):  
Artificial Intelligence ◽  
Stock Market ◽  
Financial Services ◽  
Future Research ◽  
Individual Investors ◽  
Content Type ◽  
Advisory Services ◽  
Wealth Management ◽  
Management Scenario ◽  
Indian Stock Market

Purpose The purpose of this study is to gauge the awareness and perception of Indian individual investors about a new fintech innovation known as robo-advisors in the wealth management scenario. Robo-advisors are comprehensive automated online advisory platforms that help investors in managing wealth by recommending portfolio allocations, which are based on certain algorithms. Design/methodology/approach This is a phenomenological qualitative study that used five focussed group discussions to gather the stipulated information. Purposive sampling was used and the sample comprised investors who actively invest in the Indian stock market. A semi-structured questionnaire and homogeneous discussions were used for this study. Discussion time for all the groups was 203 min. One of the authors moderated the discussions and translated the audio recordings verbatim. Subsequently, content analysis was carried out by using the NVIVO 12 software (QSR International) to derive different themes. Findings Factors such as cost-effectiveness, trust, data security, behavioural biases and sentiments of the investors were observed as crucial points which significantly impacted the perception of the investors. Furthermore, several suggestions on different ways to enhance the awareness levels of investors were brought up by the participants during the discussions. It was observed that some investors perceive robo-advisors as only an alternative for fund/wealth managers/brokers for quantitative analysis. Also, they strongly believe that human intervention is necessary to gauge the emotions of the investors. Hence, at present, robo-advisors for the Indian stock market, act only as a supplementary service rather than a substitute for financial advisors. Research limitations/implications Due to the explorative nature of the study and limited participants, the findings of the study cannot be generalised to the overall population. Future research is imperative to study the dynamic nature of artificial intelligence (AI) theories and investigate whether they are able to capture the sentiments of individual investors and human sentiments impacting the market. Practical implications This study gives an insight into the awareness, perception and opinion of the investors about robo-advisory services. From a managerial perspective, the findings suggest that additional attention needs to be devoted to the adoption and inculcation of AI and machine learning theories while building algorithms or logic to come up with effective models. Many investors expressed discontent with the current design of risk profiles of the investors. This helps to provide feedback for developers and designers of robo-advisors to include advanced and detailed programming to be able to do risk profiling in a more comprehensive and precise manner. Social implications In the future, robo-advisors will change the wealth management scenario. It is well-established that data is the new oil for all businesses in the present times. Technologies such as robo-advisor, need to evolve further in terms of predicting unstructured data, improvising qualitative analysis techniques to include the ability to gauge emotions of investors and markets in real-time. Additionally, the behavioural biases of both the programmers and the investors need to be taken care of simultaneously while designing these automated decision support systems. Originality/value This study fulfils an identified gap in the literature regarding the investors’ perception of new fintech innovation, that is, robo-advisors. It also clarifies the confusion about the awareness level of robo-advisors amongst Indian individual investors by examining their attitudes and by suggesting innovations for future research. To the best of the authors’ knowledge, this study is the first to investigate the awareness, perception and attitudes of individual investors towards robo-advisors.

Building (or not building) dynamic capabilities: the case of Italian subsidiaries in China and India

2018 ◽  
Vol 26 (4) ◽  
pp. 337-360 ◽  
Author(s):  
Giuseppe Tattara
Keyword(s):  
Value Chain ◽  
Multinational Enterprises ◽  
Dynamic Capabilities ◽  
Case Study Research ◽  
Business Strategies ◽  
Future Research ◽  
Capability Development ◽  
Regional Effect ◽  
Content Type ◽  
Capability Building

Purpose The purpose of this paper is to examine the process of capability building at subsidiary level and the forces preventing such process. The paper discusses and tests three propositions governing this process. Design/methodology/approach This research is based on multiple case studies. A case study research is most useful when addressing issues about which little prior theory has been developed or empirical evidence collected. Findings Subsidiaries in Asia operate in a way substantially different from those in the West. Specifically what ways do market specificities in Asian economies serve to either inhibit or positively encourage the development of a subsidiary? What are the circumstances which could induce subsidiaries to outsource production? Research limitations/implications Future research should explore the regional effect on MNE subsidiary types and different flexibilities exhibited in the value chain. What are the specific aspects (macro and micro) that explain variations of business strategies at subsidiary levelboth over time and between countries? Practical implications Multinational enterprises (MNEs) should be aware of the strong potential for capability development at the subsidiary level. This increased awareness ought to induce consideration in MNEs about how best to encourage such know capability development and how to leverage these capabilities for a better MNE performance. Social implications Managers who knew the host country languages and culture, and have outward-looking attitudes, are in advantageous positions to learn about new opportunities. Originality/value The paper offers empirical insights into the state and drivers of subsidiary performance in Asia. Specifically it shows how neglect of external conditions can act to open people’s eyes and foster a capability-building process within subsidiaries.

Coopetition among nascent craft breweries: a value chain analysis

2018 ◽  
Vol 25 (1) ◽  
pp. 2-16 ◽  
Author(s):  
David J. Flanagan ◽  
Douglas A. Lepisto ◽  
Laurel F. Ofstein
Keyword(s):  
Value Chain ◽  
Small Firms ◽  
Technology Development ◽  
Study Data ◽  
Relationship Building ◽  
Future Research ◽  
Chain Model ◽  
Value Chain Analysis ◽  
Process Technology ◽  
Content Type

Purpose The purpose of this paper is to employ an inductive approach to explore how small, nascent, firms in the craft brewing industry use cooperative behaviours with direct competitors to achieve their goals. Design/methodology/approach Data were gathered from interviews with the founders of seven small, newly established, craft brewers in a Midwestern city in the USA for this exploratory study. Data analysis followed the general tenants of inductive coding. Porter’s value chain model was used as a framework to organise and conceptualise the coopetitive behaviour uncovered. Findings The firms engage in cooperative behaviours with their direct competitors in areas such as process technology development, procurement, inbound logistics and marketing. A particularly interesting and common collaborative activity was breweries recommending/promoting competing breweries to their own customers. Practical implications This study provides clear examples of how relationship building with competitors could be advantageous and help small, nascent firms overcome the liabilities of newness and smallness. Originality/value Research on coopetition has called for a greater understanding of the nature of cooperative behaviours in small firms, start-ups and firms outside of high-technology industries. Moreover, research has called for finer-grained approaches to conceptualising coopetition. This paper fills these gaps and shows how Porter’s value chain is a useful tool for organising the types of collaborative behaviours that can be part of coopetition. The findings enhance understanding and facilitate future research by illustrating a broad array of cooperative activities that occur between direct competitors.

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

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Runyue Han ◽  
Hugo K.S. Lam ◽  
Yuanzhu Zhan ◽  
Yichuan Wang ◽  
Yogesh K. Dwivedi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Large Scale ◽  
Relevant Literature ◽  
Future Research ◽  
Specific Information ◽  
Future Directions ◽  
Content Type ◽  
B2b Marketing ◽  
Marketing Innovation ◽  
Business To Business

PurposeAlthough the value of artificial intelligence (AI) has been acknowledged by companies, the literature shows challenges concerning AI-enabled business-to-business (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/approachApplying 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.FindingsApart 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, identifying the main trends in the literature and suggesting directions for future research.Practical implicationsThrough the five identified domains, practitioners can assess their current use of AI and identify their future needs in the relevant domains in order to make appropriate decisions on how to invest in AI. Thus, the research enables companies to realise their digital marketing innovation strategies through AI.Originality/valueThe research represents one of the first large-scale reviews of relevant literature on AI in B2B marketing 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.

scholarly journals Research on the Construction Path of Ideological and Political Education for Postgraduates in the Era of Artificial Intelligence

2021 ◽  
Vol 5 (1) ◽  
pp. 14
Author(s):  
Liu Ting ◽  
Wang Anping
Keyword(s):  
Artificial Intelligence ◽  
Learning Algorithm ◽  
Evaluation Criteria ◽  
Ideological And Political Education ◽  
Political Education ◽  
Intelligent Network ◽  
Network Systems ◽  
Deep Learning Algorithm ◽  
Communication Links ◽  
Neural Network Algorithm

Postgraduate ideological and political education is an important part of ideological and political education in colleges and universities. It is the core of implementing the party’s educational policy, comprehensively improving the quality of education, and building a modern socialist education power. In the era of artificial intelligence, innovate classroom education of ideological and political education for graduate students through intelligent network systems, natural language understanding systems, and knowledge processing systems; use intelligent search systems, symbol processing systems, and combined planning systems to deepen the communication links of graduate ideological and political education; through enhancing digital intelligence tools such as genetic algorithm, deep learning algorithm and artificial neural network algorithm to reconstruct the evaluation criteria of graduate ideological and political education is an important engine to promote the intelligent, contemporary and diversified development of graduate ideological and political education in my country.

scholarly journals Corporate social responsibility in a local subsidiary: internal and external stakeholders’ power

2019 ◽  
Vol 15 (3) ◽  
pp. 377-393 ◽  
Author(s):  
Pilar Marques ◽  
Merce Bernardo ◽  
Pilar Presas ◽  
Alexandra Simon
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Value Chain ◽  
Future Research ◽  
Content Type ◽  
Beverage Industry ◽  
External Stakeholders ◽  
Food And Beverage ◽  
Local Company ◽  
Corporate Social

Purpose Using a theoretical and empirical focus on the power stakeholders exert, the purpose of this paper is to provide a better understanding of the factors that influence the subsidiaries of multinationals’ participation in corporate social responsibility (CSR) under the pressures (expectations and demands) their complex system of internal and external stakeholders’ places upon them. Design/methodology/approach Using an in-depth case study, the relationship a local subsidiary in the food and beverage industry has with its stakeholders as regards CSR is analyzed. Findings The findings illustrate three main aspects: how the local company is affected by and how it affects its stakeholders (an example of the multidirectionality of power and influence); the direct and indirect practices that are adopted to address challenges; and the importance of the role the local subsidiary plays as an implementer and diffuser of its parent organization’s responsible practices across the industry value chain. Originality/value To the best of authors’ knowledge, the focus is on analyzing the power stakeholders have in the context of multinational companies that has not been applied before, and the outcome of using this approach is that the authors have uncovered gaps in the literature for future research.

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