Shadow Business Intelligence Tool

Posted on

Shadow Business Intelligence Tool – Open Access Policy Institutional Open Access Program Special Issues Guidelines Editorial Process Research and Publication Ethics Article Processing Fees Awards Testimonials

All published articles are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of a published article, including figures and tables. For articles published under the Open Access Creative Commons CC BY license, any part of the article may be reused without permission provided the original article is clearly cited. For more information, please refer to https:///openaccess.

Shadow Business Intelligence Tool

Feature papers represent cutting-edge research with significant potential for greater impact in the field. A feature paper should be a substantial original article that covers several techniques or methods, provides an outlook for future research directions, and describes possible research applications.

Components Of The Business Intelligence Landscape

Feature papers are submitted at the personal invitation or recommendation of the Scientific Editor and must receive positive feedback from reviewers.

Editors’ Choice articles are based on recommendations from scientific editors of journals around the world. The editors select a small number of recently published articles in the journal that they believe will be particularly interesting to readers or important in the respective research field. The aim is to provide a snapshot of some of the most exciting works published in the various research areas of the journal.

Received: 20 January 2023 / Revised: 16 February 2023 / Accepted: 20 February 2023 / Published: 23 February 2023

The objective of the study is to examine the effects of business intelligence on perceptions of bank operational efficiency and profitability. The study is based on 259 responses from 27 branches of a commercial bank, using simple random sampling technique. This research uses Partial Least Squares-Structural Equation Method (PLS-SEM) method to test the hypotheses. The study examines the construct reliability and construct validity of the measurement model and examines the fitness of the construct model. The study found that business intelligence is positively associated with operational efficiency and profitability. Furthermore, the study reveals that operational efficiency through business intelligence positively affects bank profitability. Based on competitive theory, this research states that business intelligence allows a manufacturing unit to generate superior margins relative to its market competitors. Thus, banks can offer better options more cheaply than their competitors and thereby ensure a competitive advantage. Furthermore, based on the resource-based perspective theory, the study argues that business intelligence as a strategic resource provides the foundation for developing bank capabilities that lead to better performance over time. Therefore, the study suggests the application of business intelligence in banking companies and helps the effectiveness of decision making for the management organization of banks, academicians and policy makers.

Gait Recognition: A Useful Identification Tool

Banking and finance industries are undergoing transformation as a result of technological advancement [1, 2, 3]. Financial institutions now face increased competition, evolving client needs, and stringent regulatory and risk management requirements in a highly dynamic market. Simultaneously, technology has enabled the development of sophisticated business intelligence tools [4]. There are technologies that the banking and financial industry can utilize to utilize customer data to gain insights that result in more intelligent management practices and business decisions [5, 6, 7]. To that end, there are several ways that banking and financial institutions can leverage business intelligence (BI) technologies to increase profitability, mitigate risk, and gain a competitive edge. Business intelligence enables banks to respond to changing financial conditions in both normal and turbulent economic times [8].

Globally, business intelligence (BI) methods and technologies are helping banks gain a better understanding of their operations, their customers and their prospects. Additionally, BI can lead to efficiencies by highlighting areas ripe for cost reduction initiatives, new business opportunities, and more. Banking business intelligence helps users integrate multiple and disparate system sets to present dynamic data visualization dashboards that would not be able to communicate across platforms in the absence of banking business intelligence [9, 10]. Standardizing banking information is a huge task that requires multiple workers to spend several weeks each month to complete it. That is the current state of most banks trying to implement business intelligence in banking. Consider installing a software layer on top of all the different banking services’ data stores that connects them all and enables “live” reporting of all the data at the same time. Although this seems like the simplest possible solution, more work must be done to standardize the underlying data before they can be effectively used [6, 11].

Banks cannot simply add workers to increase revenue [1, 12, 13, 14]. They should always look for ways to improve the efficiency of their current workforce. Banks can use business intelligence tools to examine operational operations in order to help reduce ongoing costs and/or maximize available resources and expertise. By assessing the performance of branch workers who engage with the customer base, banks can identify ways to improve and enhance the customer experience at the contact point. Banks use business intelligence technologies to monitor customer, product and branch profitability [4, 15, 16]. Banks are increasing profitability and tracking improvement through effective pricing strategies and efficient business operations. In addition, business intelligence technologies are used for predictive analytics to determine which customers may be interested in acquiring which goods, when and how (in person, on the web or through direct mail) [5]. Banks can use this additional data to develop new and enhanced products and services that better meet customer needs and increase their market competitiveness. Armed with profitability and demographic data on its customers’ households, banks will have a better idea of ​​what a good prospect looks like and will be able to market to them more effectively. Cross-selling and up-selling efforts can be more successful if banks know which customers to target [3, 17]. Additionally, business intelligence systems can be used to analyze developments outside the bank to develop alternative investment plans. Investors can gain specific insight and construct trading signals by analyzing data from social media [18]. Through the use of analytics and business intelligence technologies, entirely new categories of investment are developing. Financial institutions must be as lean and efficient as possible in today’s hyper-competitive industry. By analyzing operational processes with business intelligence tools, banks can reduce ongoing costs and increase available resources and knowledge [19]. By assessing the performance of customer-facing staff such as sales representatives, tellers and account managers, organizations can identify ways to improve and enhance the customer experience at the contact point.

A limited amount of business intelligence (BI) studies have been found in Bangladesh [12, 20, 21, 22, 23, 24]. Thumpa, Saifujjaman [20] studied BI involving the mental health sector in Bangladesh; Arefin, Hoque [21] A study on organizational culture and BI; Al-Hasan, Akhtar [22] presented a BI model for textile industries; Babu [12] stated the challenges of artificial intelligence in Bangladesh; Nahar, Naheen [23] studied artificial intelligence and fire surveying; and Biswas, Rahman [24] stated the roles of emotional intelligence. However, there is a gap regarding the relationship of business intelligence with perceptions of operational efficiency and profitability of Bangladeshi banks.

Solved: White Page Shadow With Dark Theme?

Furthermore, few studies on business intelligence have been found internationally [17, 18, 25, 26, 27, 28, 29, 30]. Lim, Chen [18] studied on business intelligence analysis and operations but did not link profitability; Ranjan [25] showed the link between BI and strategic decision making; Elbashir, Collier [17] found a link between BI and bank performance; Sahay and Ranjan [26] studied on BI and supply chain analytics; Nofal and Yusof [27] researched BI and enterprise resource planning; Işık, Jones [28] found links of BI with environmental decision making and operational efficiency; Olszak [29] studied the application of BI by collecting qualitative data; Yiu, Yeung [31] connect BI and profitability; and Lawrence [30] found that BI was associated with operational efficiency in hospitals. Thus, there is a gap in the business intelligence literature internationally on the association of BI with bank operational efficiency and profitability.

The study found a lack of business intelligence studies in banking companies both nationally (Bangladesh) and internationally. Furthermore, Thumpa, Saifuzaman [20], Al-Hasan, Akhtar [22], Biswas, Rahman [24], Lim, Chen [18], Elbashir, Collier [17], Olszak [29] and Lawrence [30] suggested . Further study as BI has implications for businesses. In Bangladesh, banking companies are going to implement BI to achieve a strong business framework. Thus, the study developed a research model (see Figure 1) that links business intelligence with operational efficiency and profitability of banks. More specifically, the study seeks answers to the following questions: “What is the impact of business intelligence on the operational efficiency of banks?” and “What is the impact of business intelligence on banks’ profitability?” Thus, the study aims to examine the effects of business intelligence on operational efficiency and profitability of banks. Figure 1 shows the conceptual model of the study.

The study uses 259 responses from general manager, senior officers, general officers and employees of 27 branches of commercial bank in Bangladesh using simple random sampling technique. This research uses

Business intelligence reporting tool, microsoft business intelligence tool, business intelligence tool comparison, shadow intelligence book, free business intelligence tool, oliver harris a shadow intelligence, tableau business intelligence tool, best business intelligence tool, oracle business intelligence tool, excel business intelligence tool, business intelligence dashboard tool, business intelligence tool

Leave a Reply

Your email address will not be published. Required fields are marked *