Tax complexities in the Malaysian corporate tax system: minimise to maximise

2014 ◽  
Vol 56 (1) ◽  
pp. 50-65 ◽  
Author(s):  
Khadijah Isa
Keyword(s):  
Tax Compliance ◽  
Practical Experience ◽  
Assessment System ◽  
Three Dimensions ◽  
Second Phase ◽  
Corporate Tax ◽  
Two Phase ◽  
Content Type ◽  
Record Keeping ◽  
Laws And Policies

Purpose – This paper aims to examine areas of tax difficulties encountered by corporate taxpayers in complying with tax obligations under the self-assessment system. Design/methodology/approach – A two-phase exploratory mixed methods approach was employed. The first phase involves eight focus group interviews with 60 tax auditors from the Inland Revenue Board of Malaysia (IRBM) and the second phase adopts a mixed-mode survey among selected Malaysian corporate taxpayers. Thematic analysis and descriptive and inferential analysis were used to examine the qualitative and quantitative data in achieving the objective. Findings – Three dimensions of tax complexity encountered by corporate taxpayers were tax computations, record keeping and tax ambiguity. The first two complexity dimensions were faced largely by smaller companies. On the other hand, the least difficult tax-related areas were dealing with tax agents, submitting tax returns within the given time and dealing with the tax authority. Practical implications – In a tax policy context, this study enables international tax authorities in general, and Malaysian tax authority in particular, to have greater confidence in developing and administering tax laws and policies to maintain and/or increase the overall level of corporate tax compliance. Originality/value – Unlike prior studies that mainly used individual taxpayers or students as research participants, this study employed corporate tax auditors from the tax authority and corporate tax officers. Tax auditors and corporate taxpayers provide invaluable insights into the possible determinants of compliance variables. These insights are based on their practical experience in handling corporate tax audits and managing corporate tax matters, respectively.

Operations strategy of cloud-based firms: achieving firm growth in the Big Data era

2019 ◽  
Vol 40 (6) ◽  
pp. 873-896 ◽  
Author(s):  
Yongyi Shou ◽  
Xinyu Zhao ◽  
Lujie Chen
Keyword(s):  
Big Data ◽  
Content Analysis ◽  
Operations Management ◽  
Firm Growth ◽  
Seemingly Unrelated Regression ◽  
Second Phase ◽  
Operations Strategy ◽  
Two Phase ◽  
Content Type ◽  
Operations Capabilities

Purpose Cloud computing is a major enabling technology for Industry 4.0 and the Big Data era. However, cloud-based firms, who establish their businesses on cloud platforms, have received scant attention in the extant operations management (OM) literature. To narrow this gap, the purpose of this paper is to investigate cloud-based firms from an operations strategy perspective. Design/methodology/approach A two-phase multi-method approach was adopted. In the first phase, content analysis of 27 reports from cloud-based firms was conducted, aided by text mining keyword extraction. Two data-related operations capabilities were identified and hypotheses were posited regarding the relationships between data resources (DR), operations capabilities and firm growth (FG). In the second phase, a sample of 190 cloud-based firms was collected. Seemingly unrelated regression and bootstrapping method were employed to test the proposed hypotheses using the survey data. Findings The content analysis indicates data as a key resource and both data processing capability and data transformational capability as critical operations capabilities of cloud-based firms. FG is regarded as a top priority in the cloud context. The regression results indicate that DR and the two capabilities contribute to the growth of cloud-based firms. Moreover, a follow-up bootstrapping analysis reveals that the mediating effects of the two capabilities vary between different types of FG. Originality/value To the authors’ best knowledge, this is one of the first OM studies on cloud-based firms. This study extends the operations strategy literature by identifying and testing the key operations capabilities and priorities of cloud-based firms. It also provides insightful implications for industrial practitioners.

An integrative model in predicting corporate tax fraud

2014 ◽  
Vol 21 (4) ◽  
pp. 424-432 ◽  
Author(s):  
Nor Azrina Mohd Yusof ◽  
Ming Ling Lai
Keyword(s):  
Action Theory ◽  
Tax Compliance ◽  
Organizational Factors ◽  
Integrative Model ◽  
Corporate Tax ◽  
Content Type ◽  
Corporate Managers ◽  
Control Factors ◽  
Tax Fraud ◽  
The Government

Purpose – This paper aims to present an integrative model in predicting corporate tax fraud. Design/methodology/approach – This paper is grounded on three theories, namely, the theory of reasoned action, theory of planned behaviour and the “Fraud Diamond Theory”. Findings – By integrating these three theories, this paper proposes that individual cognitive factors, fraud diamond factors and organizational factors such as normative and control factors influence managers to commit corporate tax fraud. Practical implications – Practically, the proposed integrative model enables the government and tax authority to understand on why corporate managers engage in corporate tax fraud. It will also allow them to devise practical methods and strategies to prevent the corporate managers to engage in tax fraud. Originality/value – This study has merit that proposed an integrative model in predicting corporate tax fraud. Research on corporate tax fraud has been the subject of limited investigation; hence, this study contributes to the tax compliance literature by proposing an integrative model to study corporate tax fraud in a Malaysian tax setting. Future studies can be conducted to test the proposed integrative model in examining the circumstances of managers’ intention to commit corporate tax fraud.

Green supplier selection using an AHP-Entropy-TOPSIS framework

2015 ◽  
Vol 20 (3) ◽  
pp. 327-340 ◽  
Author(s):  
James Freeman ◽  
Tao Chen
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Selection Criteria ◽  
Second Phase ◽  
Structured Interviews ◽  
Entropy Weight ◽  
Two Phase ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Green Supplier Selection

Purpose – This paper aims to focus on development of a green supplier selection model using an index system based on a combination of traditional supplier and environmental supplier selection criteria. Strategies that balance economic and environmental performance are increasingly sought after as enterprises that increasingly focus on the sustainability of their operations. Green supply chain management (GSCM) in particular, enables the integration of environmentally friendly suppliers into the supply chain to be systematised to fit with specific environmental regulations and policies. More persuasively, GSCM allows enterprises to improve profits whilst lowering impacts on the global environment. Design/methodology/approach – A two-phase survey approach was adopted for the research. For the first phase, semi-structured interviews with senior management representatives of the case company – a Chinese-based electronic machinery manufacturer – were used to determine green supplier selection criteria. For the second phase, a two-part questionnaire survey was undertaken, the first part providing the data for an analytic hierarchy process (AHP) analysis of the first-phase criteria and the second with collecting data for an Entropy weight analysis. The resultant AHP and Entropy weights were then combined to form compromised weights – which, using technique for order preference by similarity to the ideal solution (TOPSIS) methodology, were translated into preferential rankings of suppliers. Findings – Senior managers were found to rank traditional criteria more highly than environmental alternatives – the implication being that for the company, concerned, it may take some time before environmental awareness is fully assimilated into GSCM practice. Originality/value – The paper moves us a significant step closer to the application more widely, of innovative AHP-Entropy/TOPSIS methodology to real-world SCM problems.

SenU-PTM: a novel phrase-based topic model for short-text topic discovery by exploiting word embeddings

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Heng-Yang Lu ◽  
Yi Zhang ◽  
Yuntao Du
Keyword(s):  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Second Phase ◽  
Word Embeddings ◽  
Two Phase ◽  
Content Type ◽  
Short Text ◽  
Topic Discovery ◽  
Two Phases ◽  
Sense Unit

PurposeTopic model has been widely applied to discover important information from a vast amount of unstructured data. Traditional long-text topic models such as Latent Dirichlet Allocation may suffer from the sparsity problem when dealing with short texts, which mostly come from the Web. These models also exist the readability problem when displaying the discovered topics. The purpose of this paper is to propose a novel model called the Sense Unit based Phrase Topic Model (SenU-PTM) for both the sparsity and readability problems.Design/methodology/approachSenU-PTM is a novel phrase-based short-text topic model under a two-phase framework. The first phase introduces a phrase-generation algorithm by exploiting word embeddings, which aims to generate phrases with the original corpus. The second phase introduces a new concept of sense unit, which consists of a set of semantically similar tokens for modeling topics with token vectors generated in the first phase. Finally, SenU-PTM infers topics based on the above two phases.FindingsExperimental results on two real-world and publicly available datasets show the effectiveness of SenU-PTM from the perspectives of topical quality and document characterization. It reveals that modeling topics on sense units can solve the sparsity of short texts and improve the readability of topics at the same time.Originality/valueThe originality of SenU-PTM lies in the new procedure of modeling topics on the proposed sense units with word embeddings for short-text topic discovery.

Anti money laundering using a two-phase system

2015 ◽  
Vol 18 (3) ◽  
pp. 304-329 ◽  
Author(s):  
Tamer Hossam Moustafa ◽  
Mohamed Zaki Abd El-Megied ◽  
Tarek Salah Sobh ◽  
Khaled Mohamed Shafea
Keyword(s):  
Money Laundering ◽  
False Positive ◽  
Phase System ◽  
Second Phase ◽  
Two Phase ◽  
Content Type ◽  
Risk Scoring ◽  
Two Phases ◽  
Clear Shift ◽  
Monitoring Phase

Purpose – This paper aims to compete and detect suspicious transactions that can lead to detecting money laundering cases. Design/methodology/approach – This paper presents a plan-based framework for anti-money laundering systems (PBAMLS). Such a framework is novel and consists of two phases, in addition to several supporting modules. The first phase, the monitoring phase, utilizes an automata approach as a formalism to detect probable money laundering. The detection process is based on a money laundering deterministic finite automaton that has been obtained from the corresponding regular expressions which specify different money laundering processes. The second phase is STRIPS-based planning phase that aims at strengthening the belief in the probable problems discovered in the first (monitoring) phase. In addition, PBAMLS contains several supporting modules for data collection and mediation, link analysis and risk scoring. To assess the applicability of PBAMLS, it has been tested using different cases studies. Findings – This framework provides a clear shift of anti-money laundering systems (AML) from depending heuristic and human expertise to making use of a rigorous formalism to accomplish concrete decisions. It minimizes the possibilities of false positive alarms and increases the certainty in decision-making. Practical implications – This framework enhances the detection of money laundering cases. It also minimizes the number of false-positive alarms that waste the investigators’ efforts and time; it decreases the efforts presented by the investigators. Originality/value – This work proposes PBAMLS as a novel plan-based framework for AML systems.

Terrorism, competitiveness, and international marketing: an empirical investigation

2018 ◽  
Vol 13 (2) ◽  
pp. 310-329
Author(s):  
Valbona Zeneli ◽  
Michael R. Czinkota ◽  
Gary Knight
Keyword(s):  
Empirical Research ◽  
Multinational Enterprises ◽  
Online Survey ◽  
Early Stage ◽  
Qualitative Interviews ◽  
International Marketing ◽  
Second Phase ◽  
Two Phase ◽  
Content Type ◽  
The Relationship

Purpose The purpose of this paper is to research the relationship between terrorism and multinational enterprises (MNEs), focusing on operational costs, marketing planning, supply chain management, and distribution activities. Terrorism is a growing threat to internationally active firms, but there has been no empirical research to address the distinctive challenges that terrorism poses for the international marketing activities of firms. Design/methodology/approach The paper opted for an exploratory investigation, following a two-phase research design. In the first phase it was based on qualitative interviews with internationally active firms. In the second phase, an online survey of a large sample of international firms based in the USA was performed. All measures were developed specifically for the study. Findings The paper provides empirical insights about how terrorism affects MNEs, especially those operating in emerging markets. It suggests that terrorism accounts for significant costs in the international marketing budget of MNEs, as well as in planning, and the design of supply chains and distribution channels. Findings also reveal that firms with significant resources and international experience appear to cope better with terrorism’s effects. Research limitations/implications Given the early stage of empirical research on terrorism and international marketing, this study was necessarily exploratory. Practical implications The paper includes implications and suggestions for multinational companies to increase the security of their businesses through the development of corporate preparedness. Social implications Terrorism represents not only an organizational crisis at the level of a firm, but it affects the whole society. Originality/value This paper fulfills an identified need to study the relationship between the growing threat of terrorism and international business.

What make investors herd while investing in the Indian stock market? A hybrid approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muskan Sachdeva ◽  
Ritu Lehal ◽  
Sanjay Gupta ◽  
Aashish Garg
Keyword(s):  
Stock Market ◽  
Fuzzy Ahp ◽  
Hybrid Approach ◽  
North India ◽  
Second Phase ◽  
Herd Behavior ◽  
Herding Behavior ◽  
Two Phase ◽  
Content Type ◽  
Indian Stock Market

PurposeIn recent years, significant research has focused on the question of whether severe market periods are accompanied by herding behavior. As herding behavior is a considerable cause of the speculative bubble and leads to stock market deviations from their basic values it is necessary to examine the motivators which led to herding behavior among investors. The paper aims to discuss this issue.Design/methodology/approachIn this study, the authors performed a two-phase analysis to address the research questions of the study. In the first phase, for text analysis NVivo software was used to identify the factors driving herding behavior among Indian stock investors. The analysis of a text was performed using word frequency analysis. While in the second phase, the Fuzzy-AHP analysis techniques were employed to examine the relative importance of all the factors determined and assign priorities to the factors extracted.FindingsResults of the study depicted Investor Cognitive Psychology (ICP), Market Information (MI), Stock Characteristics (SC) as the top-ranked factors driving herding behavior, while Socio-Economic Factors (SEF) emerged as the least important factor driving herding behavior.Research limitations/implicationsThe current study was undertaken among stock investors from North India only. Moreover, numerous factors are not part of the study but might significantly influence the investors' herding behaviors.Practical implicationsComprehending the influences of the different factors discussed in the study would enable stock investors to be more aware of their investment choices and not resort to herd behavior. This research enables decision-makers to understand the reasons for herd activity and helps them act accordingly to improve the stock market's performance.Originality/valueThe current study will provide an inclusive overview of herding behavior motivators among Indian stock investors. This study's results can be extremely useful for both academics and policymakers to gain some insight into the functioning of the Indian stock market.

A bid generation problem for combinatorial transportation auctions considering in-vehicle consolidations

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fang Yan ◽  
Kai Chen ◽  
Manjing Xu
Keyword(s):  
Computation Time ◽  
Mixed Integer ◽  
Small Scale ◽  
Second Phase ◽  
Two Phase ◽  
Content Type ◽  
Numerical Examples ◽  
Proposed Model ◽  
Vehicle Capacity ◽  
Generation Problem

PurposeThis paper studied a bid generation problem in combinatorial transportation auctions that considered in-vehicle consolidations. The purpose of this paper seeks to establish mixed integer programming to the most profitable transportation task packages.Design/methodology/approachThe authors proposes a mathematical model to identify the most profitable transportation task packages under vehicle capacity, flow balance and in-vehicle consolidation operational constraints, after which a two-phase heuristic algorithm was designed to solve the proposed model. In the first phase, a method was defined to compute bundle synergy, which was then combined with particle swarm optimization (PSO) to determine a satisfactory task package, and in the second phase, the PSO was adopted to program vehicle routings that considered in-vehicle consolidation.FindingsThree numerical examples were given to analyze the effects of the proposed model and method, with the first two small-scale examples coming from the same data base and the third being a larger scale example. The results showed that: (1) the proposed model was able to find a satisfactory solution for the three numerical examples; (2) the computation time was significantly shorter than the accurate algorithm and (3) considering in-vehicle consolidations operations could increase the carrier profits.Originality/valueThe highlights of this paper are summarized as following: (1) it considers in-vehicle consolidation when generating bids to maximize profits; (2) it simultaneously identifies the most valuable lane packages and reconstructs vehicle routes and (3) proposes a simple but effective synergy-based method to solve the model.

Developing a two-phase QFD for improving FMEA: an integrative approach

2019 ◽  
Vol 36 (8) ◽  
pp. 1454-1474 ◽  
Author(s):  
Fatemeh Shaker ◽  
Arash Shahin ◽  
Saeed Jahanyan
Keyword(s):  
Literature Review ◽  
Failure Modes ◽  
Continuous Production ◽  
Integrative Approach ◽  
Importance Rating ◽  
Second Phase ◽  
Extensive Literature ◽  
Two Phase ◽  
Content Type ◽  
Wide Range

Purpose The purpose of this paper is to propose an integrative approach for improving failure modes and effects analysis (FMEA). Design/methodology/approach An extensive literature review on FMEA has been performed. Then, an integrative approach has been proposed based on literature review. The proposed approach is an integration of FMEA and quality function deployment (QFD). The proposed approach includes a two-phase QFD. In the first phase, failure modes are prioritized based on failure effects and in the second phase, failure causes are prioritized based on failure modes. The proposed approach has been examined in a case example at the blast furnace operation of a steel-manufacturing company. Findings Results of the case example indicated that stove shell crack in hot blast blower, pump failure in cooling water supply pump and bleeder valves failed to operate are the first three important failure modes. In addition, fire and explosion are the most important failure effects. Also, improper maintenance, over pressure and excess temperature are the most important failure causes. Findings also indicated that the proposed approach with the consideration of interrelationships among failure effects, failure mode and failure causes can influence and adjust risk priority number (RPN) in FMEA. Research limitations/implications As manufacturing departments are mostly dealing with failure effects and modes of machinery and maintenance departments are mostly dealing with causes of failures, the proposed model can support better coordination and integration between the two departments. Such support seems to be more important in firms with continuous production lines wherein line interruption influences response to customers more seriously. A wide range of future study opportunities indicates the attractiveness and contribution of the subject to the knowledge of FMEA. Originality/value Although the literature indicates that in most of studies the outcomes of QFD were entered into FMEA and in some studies the RPN of FMEA was entered into QFD as importance rating, the proposed approach is a true type of the so-called “integration of FMEA and QFD” because the three main elements of FMEA formed the structure of QFD. In other words, the proposed approach can be considered as an innovation in the FMEA structure, not as a data provider prior to it or a data receiver after it.

Quantitative assessment of spiritual capital in changing organizations by principal component analysis and fuzzy clustering

2015 ◽  
Vol 28 (3) ◽  
pp. 469-485 ◽  
Author(s):  
Mohammad Reza Taghizadeh Yazdi
Keyword(s):  
Principal Component Analysis ◽  
Fuzzy Clustering ◽  
Questionnaire Survey ◽  
Quantitative Assessment ◽  
Principal Component ◽  
Component Analysis ◽  
Second Phase ◽  
Two Phase ◽  
Content Type ◽  
Spiritual Capital

Purpose – The purpose of this paper is to illustrate the application of statistical tools and techniques for quantitative assessment of spiritual capital (SC) based on a questionnaire survey in the organizations which undergo large-scale organizational change projects. Design/methodology/approach – A sample of 65 individuals from three organizations were interviewed. The paper uses the 12 principles of transformation available to spiritual intelligence (referred to as SQ characteristics) to assess SC in a two-phase integrated algorithm of principal component analysis (PCA) and fuzzy clustering. Findings – The paper proposes a two-phase integrated algorithm. In the first phase, PCA is used to reduce the scores of items related to each of SQ characteristics and aggregate them into a single and unique measure. In the second phase, PCA is applied for total SQ quantification. For verification and validation, fuzzy clustering is employed along with PCA to cluster the people in the survey into different classes, which may possess different stocks of SC and rank them based on their level of SQ. The results of PCA are verified and validated by fuzzy clustering revealing the applicability and usefulness of PCA for SC quantification. Research limitations/implications – The paper is based on individual judgments about their own SQ characteristics hence the results of questionnaire survey may be biased by individual personal characteristics. Future research can apply the proposed algorithm and check for its reliability using other psychometric instruments available in the field. Originality/value – The paper contributes by filling a gap in the quantitative management tools literature, in which empirical studies on validated multivariate analysis of spirituality have been scarce until now.

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