Robotic process automation adoption: contextual factors from service sectors in an emerging economy

Sharma, Chitra; Bharadwaj, Sangeeta Shah; Gupta, Narain; Jain, Hemant

doi:10.1108/jeim-06-2021-0276

Cited by 16 publications

(17 citation statements)

References 51 publications

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“…Moreover, lack of good warehousing management gives rise to various problems including but not limited to food waste due to expiration, and ineffective and inefficient storage of food. AI is increasingly deployed to reduce various tasks' labour-intensiveness, though it typically requires huge amounts of data (Chang et al, 2021;Pal et al, 2023;Qamar et al, 2021;Sharma et al, 2022). In that vein, this paper focuses on enabling machines to learn how inbound logistics tend to be dealt with by human beings.…”

Section: Methodsmentioning

confidence: 99%

“…Prominent among the widespread applications of AI to date are quality-control improvement (Wu and Chien, 2021) and labour-shortage mitigation (Chang et al, 2021;Qamar et al, 2021;Sharma et al, 2022). Because food banks suffer chronic shortages of experienced personnel, it is challenging for them to effectively evaluate the quality donated food or to organise their stocks of it; and AI offers a potential solution.…”

Section: Research Gapsmentioning

confidence: 99%

“…An expanding range of artificial intelligence (AI) applications is making humans' work easier (Chang et al, 2021;Qamar et al, 2021;Sharma et al, 2022). Such applications also have strong potential to achieve this in the case of food banks' inbound logistics: specifically, by taking in expert knowledge donated foods' quality of donated food, processing that data and using the processing results to boost warehousing-management performance.…”

Section: Introductionmentioning

confidence: 99%

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Artificial intelligence-based food-quality and warehousing management for food banks' inbound logistics

Wu,

Tai

2024

JEIM

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PurposeIn the reduction of food waste and the provision of food to the hungry, food banks play critical roles. However, as they are generally run by charitable organisations that are chronically short of human and other resources, their inbound logistics efforts commonly experience difficulties in two key areas: 1) how to organise stocks of donated food, and 2) how to assess the donated items quality and fitness for purpose. To address both these problems, the authors aimed to develop a novel artificial intelligence (AI)-based approach to food quality and warehousing management in food banks.Design/methodology/approachFor diagnosing the quality of donated food items, the authors designed a convolutional neural network (CNN); and to ascertain how best to arrange such items within food banks' available space, reinforcement learning was used.FindingsTesting of the proposed innovative CNN demonstrated its ability to provide consistent, accurate assessments of the quality of five species of donated fruit. The reinforcement-learning approach, as well as being capable of devising effective storage schemes for donated food, required fewer computational resources that some other approaches that have been proposed.Research limitations/implicationsViewed through the lens of expectation-confirmation theory, which the authors found useful as a framework for research of this kind, the proposed AI-based inbound-logistics techniques exceeded normal expectations and achieved positive disconfirmation.Practical implicationsAs well as enabling machines to learn how inbound logistics are handed by human operators, this pioneering study showed that such machines could achieve excellent performance: i.e., that the consistency provided by AI operations could in future dramatically enhance such logistics' quality, in the specific case of food banks.Originality/valueThis paper’s AI-based inbound-logistics approach differs considerably from others, and was found able to effectively manage both food-quality assessments and food-storage decisions more rapidly than its counterparts.

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Section: Methodsmentioning

confidence: 99%

Section: Research Gapsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Artificial intelligence-based food-quality and warehousing management for food banks' inbound logistics

Wu,

Tai

2024

JEIM

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“…Another significant factor that determines an organization’s readiness for adopting blockchain technology is leadership support (Sharma et al , 2023). Leadership plays a key role in establishing the culture and values of a firm and in supporting the adoption of new technology (Clohessy and Acton, 2019; Wang et al , 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

Does the adoption of blockchain technology add intangible benefits to the industrial sector? Evidence from Jordan

Jaradat

AL-Hawamleh

Shbail

et al. 2023

JFRA

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Purpose This study aims to examine the feasibility of adopting blockchain technology in Jordan’s industrial sector and its intangible benefits. It also analyzes the influence of factors like technological, process, cultural and leadership readiness on the willingness of enterprises to adopt blockchain. Design/methodology/approach To gain insights into the potential adoption of blockchain technology and its intangible benefits for enterprises in the Jordanian industrial sector, this study gathered perspectives from a broad range of professionals, including financial managers, internal control staff, accounting departments, IT department managers and IS-related personnel. This was achieved through the administration of a comprehensive questionnaire designed to capture their opinions. Findings This study highlights the importance of technological and leadership readiness in adopting blockchain. It also shows that blockchain adoption can yield significant intangible benefits for enterprises. However, the study did not find a significant relationship between process readiness, cultural readiness and the intention to adopt blockchain. Practical implications The study’s outcomes underscore the importance of prioritizing technological and leadership readiness for enterprises and policymakers intending to adopt blockchain technology. By doing so, they can increase their willingness to adopt this technology and leverage its benefits. Originality/value This pioneering study investigates the adoption of blockchain technology and its intangible benefits for Jordanian businesses. It also examines the influence of factors like technological, process, cultural and leadership readiness on the decision to adopt blockchain in the industrial sector.

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“…RPA-based solutions are transforming business processes by delivering fast, accurate service, and improving the customer experience. Organizations are seeking to leverage the potential of RPA and provide better business and tech solutions (Bhaskar et al, 2021). More recently, industries are giving increased importance to automation as it is disrupting the current state of daily business processes, keeping well balanced with organizational drivers such as cost, productivity, and efficiency (da Silva Carvalho et al, 2021).…”

Section: Research Gapmentioning

confidence: 99%

From Hype to Reality: Navigating the Challenges of RPA Implementation

Treacy,

Adyanthaya,

Kearny

et al. 2023

ECIE

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The term Robotic Process Automation (RPA) was first utilised in 2012 (Hindle, 2018). The term began to gain traction in 2014 when businesses started to announce major savings because of automation. In early 2016, RPA back office automation became more significant but during this period it was still relatively limited (Willcocks & Lacity, 2016). From 2016 to 2017 the global RPA market increased by 64% (Fersht, 2017). They also reported a 42% increase in the global market for RPA between 2017 and 2018 and an anticipated increase of a further 94% between 2018 and 2021 (Fersht, 2017). The demand for RPA has increased using AI and software robots are expected to be the key drivers of growth. RPA continues to gather prominence throughout Europe as companies are eager to improve customer experience and to offer a streamlined service particularly for the financial services industry (Information Services Group, Inc., 2018). The key objective is to improve organizational performance and the customers’ experience using an RPA solution. The RPA solution will enable the organization to provide around the clock robot assistance to the client, enhancing effectiveness and efficiency of the compliance process, faster return on investment (ROI), reduced processing time as well as helping to meet deadlines, improved quality with reduced human errors (Pattfaut and Borghoff, 2022). However, RPA is an extensive process and requires expertise in this space, structured input, and governance to achieve optimal implementation. The research objective of this investigation therefore is to explore methods for automating business processes while reducing operating costs and improving efficiency. In doing so, three research questions are presented: 1) What are the key phases in an RPA implementation?: 2) What activities are involved in each of the phases?; and 3) What should be the focus of each of these activities?

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Robotic process automation adoption: contextual factors from service sectors in an emerging economy

Cited by 16 publications

References 51 publications

Artificial intelligence-based food-quality and warehousing management for food banks' inbound logistics

Artificial intelligence-based food-quality and warehousing management for food banks' inbound logistics

Does the adoption of blockchain technology add intangible benefits to the industrial sector? Evidence from Jordan

From Hype to Reality: Navigating the Challenges of RPA Implementation

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