IFRSs Convergence and Expectation Gap: Vindication from Practitioners

Abstract

The study has attempted to measure the Indian practitioners’ expectation gaps about IFRSs convergence. Based on literature, two hypotheses, a conceptual model and a questionnaire, have been formed. Through protocol interviews followed by a pretest, the questionnaire has been tested (reliability and validity) before conducting the online survey. A total of 159 sample responses has been assessed to measure the gaps on four major parameters. For assaying the gaps, the arithmetic and weighted arithmetic mean differences and paired sample t-test have been applied, which have indicated the likely persistence of gaps. The significant statistical results have indicated likely to reject the null hypotheses and it has to conclude that regulatory requirements have influenced in convergence and the Ind AS probably to improve the reporting practices, audit qualities and analysts’ forecasting. Study limitations, practical implications and roadmap for further research have also been indicated.

Keywords

Ind AS Online Survey Expectation Gap Measurements Inferential Statistics

Introduction

Literature has indicated that enormous amount of studies have been attempted globally addressing international accounting harmonization issues, that is, either adoption or convergence with International Financial Reporting Standards (hereafter IFRSs)^1,2, and such implementation has an effect on a country’s impression and in ease of doing businesses. International Accounting Standard Board (IASB), the issuer of IFRSs, has referred “IFRSs” as the combination of (a) IFRS, (b) International Accounting Standards, (c) interpretations originated by the International Financial Reporting Interpretation Committee (IFRIC), and (d) interpretations issued by the former Standing Interpretations Committee (SIC)³. In the process of harmonizing the domestic accounting standards (ASs) in line with IFRSs, countries adopt the standards formulated by IASB either as it is without any deviations, which is termed as adoption, or with little bit modifications as per that country’s prevailing socio-economic and legal norms, that is, convergence.The present Indian generally accepted accounting principles (GAAP) has been aligned with that of US GAAP, that is, rule based although IFRSs are principles based⁴. The Institute of Chartered Accountants of India (ICAI), the Indian accounting profession watchdog, has issued the converged versions of IFRSs (referred as Ind AS), being principle-based standards where it has set the standards and interpretations have been left to the users, that would probably reflect economic substance and the accounting principles of each transactions in a better manner than IFRSs adoption⁵. It has to be noted that an alternative principle/method that is not available in the original versions of IFRSs would not be allowed in the converged versions⁶. IASB generally has not taken into consideration country-specific socio, economic and legal aspects, hence convergence instead of adoption would be more suited for a vast country like India⁷. Moreover, nations’ skewed representations in the standard-setting exercise⁸ along with biased procedural legitimacy^9,10 might have motivated India to follow the convergence route.

Studies on IFRSs adoptions have been attempted worldwide encompassing benefits like reduction in asymmetric information^11,12 improved transparency and comparability in accounting¹³ with high-quality financial reporting¹⁴, significant improvement in investors’ information requirement¹⁵ along with voluntary disclosure practices¹⁶ and reduction in tax liabilities during post IFRSs adoption¹⁷. Literature has validated that after IFRSs, adoption audit quality has been significantly improved with reduction in audit fees¹⁸ while few scholars have been concluded with opposite results¹⁹. Scholarship has concurred that during post- IFRSs adoptions, number of accounting developments such as the valuations and recognitions of impairment losses of intangibles e. g., goodwill has been significantly been influenced²⁰, and costs of equity^21,22 with earnings management have also been reduced^23,24 and improvements have been there in the income smoothing practices²⁵—but few studies have not found any such decreasing trend in earnings management²³. Moreover, IFRSs adoption has provided easy access to international capital markets²⁶ and increased analysts’ forecast accuracy²⁷, and tie ups with banks and financial institutions have also been increased²⁸. Further, implementation challenges also have been highlighted by scholars²⁹.

Studies in Indian context have addressed converged IFRSs (Ind AS) aspects, for example, corporates’ preparedness in implementing IFRSs³⁰, implementation challenges³¹, impact on taxation³², related party disclosures under Ind AS-24,³³ curve outs and curve ins of Ind AS³⁴, issues involved for first-time adopter, that is, Ind AS-101³⁵, issues in business combinations under Ind AS-103³⁶, challenges of implementation of revenue recognition standards Ind AS-115 in general³⁷ and in Pharma sector in particular³⁸, implementation issues on consolidated financial statements under Ind AS-110³⁹, impacts on reporting practices⁴⁰, influence of country-specific factors¹, costs, IT, infrastructural and training challenges of IFRSs implementation⁴¹, effect on selective financial key ratios of Wipro⁴² and on few other companies ratio analysis using Gray index^43,44. Literature has validated perception studies on IFRSs have been primarily focused on users of financial reports⁴⁵. Studies have so far been attempted in specific aspects of Ind AS rather any comprehensive perception studies with stakeholders such as investors, financiers, tax authorities, regulators, analysts, practitioners and the like. The current research has motivated to replenish this deficiency in the literature by assaying the practitioners’ expectations about India’s IFRSs convergence and the gaps, if any by conducting an online survey using a self-designed questionnaire.

The study has contributed in the literature in the following ways. First, it has produced a ready reference of practitioners’ expectation gaps (EGs) analysis on IFRSs convergence aspects, probably for the first time in Indian context. Second, it has validated the significant influence of multiple regulations in framing Ind AS, in line with literature⁴⁶ but has differed from other few studies⁴⁷. Third, the mean analysis of EGs has indicated highest level of gaps in Ind AS while that of lowest in corporate reporting issues. Moreover, the weighted arithmetic mean (WAM) differences have pointed out positive gaps for 21 pairs, negative for 3 pairs and no such gap for one paired sample. The aforesaid measured gaps have mostly been supported by the findings of the dependent paired sample t-test. Finally, the probable improvements in audit quality and forecast accuracy have provided evidence of concurrent validities¹⁸ but has differed from studies which have concluded with increase in audit risks¹⁹.

The study has attempted to assess the practitioners’ EGs, if any regarding IFRSs convergence.

The rest of the study has been designed as the research hypotheses have been formed in the second Section; the adopted methodology has been explained in the third Section, statistical results and interpretations have been summarized in the fourth section and eventually in the fifth Section, the study has reached in its conclusion.

Background Literature and Hypotheses Construction

Related literature has been scanned to rationalize the hypotheses and to set a conceptual model for executing the study.

Ind AS and Regulatory Requirements

The curving out of IFRSs issues have been materialized in tune with prevailing legal and regulatory requirements such as custom, income tax, company law and the broader public sentiments. The affiliated member of International Federation of Accountants (IFAC) has been entrusted to promote the IFRSs, for example, ICAI for bringing accounting harmonization. The Companies (Indian Accounting Standards) Rules, 2015 and its subsequent amendments in 2017 have been issued by The Ministry of Corporate Affairs (MCA) for smooth implementation of Ind AS. Further, ICAI has unequivocally clarified that for any conflicting issues between Ind AS and different regulations, the latter would prevail^48,49, which itself has justified the rationale for setting the H1. India is one of those countries which has committed to gradual alignment with IFRSs⁵⁰ as political pressure⁵¹, continuous interaction with foreign countries and resource dependencies^4,41 have also played significant roles resulting phase-wise transition from 2016 to 2017 onwards. Different conflicting legal and regulatory requirements such as the Companies Act, Securities and the Exchange Board of India (SEBI) Act, the Insurance Regulatory and Development Authority of India (IRDA) Act, the Income Tax Act, the Reserve Bank of India (RBI) Act have significant implications on financial reporting practices and accounting discipline status in particular, and economy in general, which have been duly acknowledged by the expert bodies^48,49 while framing and implementing the Ind AS. Moreover, in line with the legal, regulatory and prevailing business environment, the industries’ preparedness has also been considered by ICAI before choosing the convergence route⁷. The literature has reported earlier Indian GAAP was successfully aligned with US GAAP which has catalyzed the foreign investments with regulatory framework conducive for operating businesses⁵². India has decided for gradual transition to IFRSs by solving the local issues, infrastructural and training problems^41,53,31. Interestingly, literature has been concluded with mix results regarding the regulatory impacts on IFRSs—an improved degree of compliance and in Brazil⁴⁶; but such compliance has been deteriorated in Turkey⁴⁷. Accordingly, it has been hypothesized that:

H1: Regulatory requirements significantly influence in the implementation of Ind AS.

Ind AS Impacts

The study has chosen three aspects, namely, reporting practices, role of company auditors and analysts’ forecasting to assess the Ind AS impacts. The rationale and background literature has been presented in the under stated manner.

Reporting Practices

ICAI’s compiled study on compliance of Financial reporting requirements⁵⁴ has documented disclosure deviations by the Indian companies especially the prevailing accounting standards such as in AS-1 the lack of revenue recognition timings, inventories valuation methods, erroneous conversions of all balance sheet items with current foreign exchange rates instead of monetary items, non-recognition of threats to going concern concept. Similarly, for other standards, non-compliance instances have also been indicated. It has been expected that Ind AS would significantly improve the compliances leading to better disclosures as evidenced from IFRSs-adopting countries that have motivated the present study to frame the H2. Again, literature has validated multi-dimensional impacts of IFRSs on corporate reporting and disclosure practices such as signi-ficant improvements in transparency, comparability and reporting quality^24,55,13 and reductions in accounting subjectivity^56,57. The association between financial figures and intrinsic values of the firms⁵⁸ and earnings information^59,11 has been significantly improved. Moreover, the effects on corporates’ equity, increased earnings fluctuations and decreased conservatism¹² along with poor accounting quality⁶⁰ and lesser accounting comparability in subsequent years⁶¹ have also been reported.

Role of Company Auditor

The accounting professionals would likely to be easily accessible globally with their expertise due to harmonization of the accounting system^54,62. Their services would be required in different Ind AS-emerged accounting supports, for example, for first-time adoptions, preparation of consolidated financial statements applying IFRSs and Ind AS, closing of financial statements and carrying out internal and statutory audits⁶³. Literature has reported Indian corporate governance (CG) failure like the United Spirits Ltd.¹ and high expectations from statutory auditors for fraud detection and curbing after the exposure of infamous Satyam Computer scam⁶⁴. The current study has hypothesized that Ind AS would significantly influence the role of company auditors with a proxy of high-audit quality, in line with worldwide evidence as enumerated. IFRSs impacts on audit fees and audit quality have been studied globally in delve⁶⁵. The audit quality has significantly been improved especially in Western countries as trained auditors have been performing the audit works¹⁸ resulting in reduction in audit fees⁶⁶. In contrast, few studies have reported increase in audit fees^67,19 with enhanced audit risks¹⁸ and have increased adoption errors leading to enhanced audit fee⁶⁸ probably due to the presence of subjectivity^69,70.

Analysts’ Forecasting

Indian accounting experts have expected significant increase in analysts’ forecasting roles in terms of quality and quantity in Ind AS era^48,71. The professionals would share their acumen in multiple analytical works such as business valuation, consultations, valuation of securities, money market expert and in corporate tax planning post Ind AS period⁵ resulting enhancement in their forecasting accuracy as hypothesized in the study. Literature has documented that IFRSs impact studies addressing analysts’ forecasting such as improvements in forecasting accuracy^72,15, decreased forecasting errors²⁷, improved analysts’ performances^50,73, managers’ improved tendency for earnings guidance⁷⁴, attraction of foreign analysts voluntarily⁷⁵ and mandatorily IFRSs-adopting firms⁷³ have been reported. Based on all these, it has been hypothesized that:

H2: The applications of Ind AS significantly improve the corporate reporting practices, audit quality and analysts’ forecasting.

Figure 1 has presented a conceptual model for carrying out the study, that is, to assess the practitioners’ EGs, if any in regards to IFRSs convergence. Regulatory requirements have been assumed as predictor which has an effect on implementation of Ind AS and the latter being a predictor likely to have significant impacts on three outcomes. It has taken a research paradigm where the ontology has assumed as the practitioners’ EGs (existence of reality), with an epistemology to study those gaps (assemble of knowledge), has an axiology (objectives of the study), has adopted an appropriate methodology to execute the study (an approach of carrying out the research) followed by a method (data collection and analysis techniques).

Methodology

Research methodology which has been defined as a holistic approach relevant for executing a study from theoretical underpinnings to its conclusion⁷⁶ having different subsections as under.

Study Design

Adopting a cross-sectional study design with online survey strategy during the period January–mid June, 2017 responses have been gathered. Survey strategy with multiple benefits like easy quantification⁷⁷, holistic coverage of research problem⁷⁸ and high degree of external validities⁷⁹ have been applied. Moreover, substantial accounting and auditing studies have used online surveys^80,81.

Methods

Literature has explained methods as a tool for data collection and analysing technique⁸², incorporating therein the following sub-heads.

Questionnaire Design

The questionnaire has developed in the following manner. First, accessing digital library of a central university and by searching with few relevant key words, 319 IFRSs-related papers having full texts published by Springer, Emerald, Wiley, Taylor & Francis, Elsevier science direct, SAGE Publications, Oxford University Press have been downloaded. Moreover, around 129 expert opinions published in four English business newspapers and ICAI materials and articles have also been shortlisted. Second, after reviewing, these 60-item questionnaire have been prepared in five-point Likert scale. Third, protocol interviews with three subject experts have been conducted to refine the questions as suggested by scholar⁸³, and based on mean results, four questions have been deleted. Fourth, a pilot study with 30 randomly chosen sample respondents has been conducted to test the reliability of the questionnaire as scholars indicated⁸⁴, and based on minimum Cronbach alpha scores of 0.5, it has dropped six more questions. Finally, the questionnaire has been attached in Google docs and has been mailed to the prospective respondents.

Sampling Design

All the practising chartered accountants (CAs), management accountants (CMA), chartered secretaries (CS), certified financial analysts (CFA) and other practitioners with post graduate and PhD degrees have been assumed as study population. Since the name and contact details of all of them have been inaccessible, it has not set the sampling frame and rather has chosen a non-probability sampling technique, that is, convenience sampling technique. By accessing different sources, the enumerator has gathered 337 mail ids and has emailed along with a cover letter incorporating study objective, instruction for filling the questionnaire have used, as suggested by authors⁸⁵. Further, they have been assured about data collection and analysis ethicality as literature indicated⁸⁶. A total of 159 responses (47.18%) has so far been received (till 31 May 2017) which has been treated as the eventual sample size; an adequate figure within the threshold limit of between 30 and 500 to carry out a social science research as authors advocated^87,88,89. Further, it has applied wave analysis method to determine response bias and five responses received after the dead line have been ignored.

Data

Primary Data

It has developed a self-administered questionnaire having three sections. Section I has 10 demographic questions and in Sections II and III, each has 25 pair questions (divided into four subsections each) addressing IFRSs expectations and perceptions, respectively, have designed in five-point Likert scale as it has multiple advantages as concluded by authors⁹⁰. Even though the questions have been divided into eight subsections, the same has not been exhibited to the respondents for getting unbiased responses.

Secondary Data

The study has reviewed a number of secondary data.

Primary sources: Research papers published in different academic and professional journals have been reviewed.

Secondary sources: At least five review papers on IFRSs and expert opinions published in different business newspapers, monographs and relevant websites like www.ifrs.org have also been reviewed.

Tertiary Sources: Different databases such as social science research network (SSRN), Indian Citation Index (ICI), Google Scholar, Scopus, J-Gate and INFLIBNET E-Soudhsindhu have consulted.

Data Analysis Strategy

It has applied IBM Statistical Package for Social Science (SPSS) version 20 for data analysis.

Variables

The variables of the study have been categorized into predictor, outcome and confounding as presented in Table 1.

Table 1.

Study Variables

Predictors	Outcomes	Confounding
Regulatory requirements	Ind AS	Institutional isomorphism (coercive, mimetic and normative)
Ind AS	Reporting practices
	Audit quality
	Analysts’ forecasting

Source: The authors.

Regulatory requirements are those rules framed by the different regulatory bodies, for example, ICAI, SEBI, RBI and other statutory requirements like Companies Act enforced through MCA for implementing Ind AS. The converged versions of IFRSs—modified from original versions (curve out)—are known as Ind AS framed by Indian accounting profession regulator ICAI applicable to specific class of companies from the financial year 2016–2017 onwards and extendable to other class of companies from subsequent years. Reporting practices in its common parlance indicate the corporate reporting, that is, presentation and disclosure aspects as distinct from accounting and measurements normally incorporated therein the integrated reporting, financial reporting, corporate governance practices, corporate social responsibility, remuneration of executives and accounting narratives. Although there is no uniform definition of audit quality, it usually refers the degree of confidence shown by the users of financial statements on audit works. Analysts’ forecasting refers their predictions about a company’s (s)/industry’s (s) speed of production, growth rates, demands, earnings potentials, estimated market price of shares and the like. Coercive isomorphism is an outcome of formal and informal pressure on an organization for adopting the same accounting system on which it has been largely dependent as well as implied pressure of the society in which it has been operating^91,92. Mimetic isomorphism has been taken place when a relatively new or less successful organization has followed a successful organization especially during uncertain environment^91,93. Normative isomorphism has been referred as the level of education attainment of a country, that is, to say the percentage of the population that have been educated have also affected accounting practices resulting adoptions of IFRSs.

Significance Level

It has assumed significance level (α) as 5 per cent, that is, in other words, confidence level has assumed as 95 per cent.

Choice of Statistical Tests

Research Validities

The study has derived multiple research validities, for example, construct (items in the questionnaire), content (scope to address the research questions), instrument (use of identical questionnaire for pilot and final survey), internal (findings), concurrent (correlated significant findings) and conclusions (generalization of findings). For countering the internal validity threats, respondents have chosen randomly and judiciously and for external validity threats, the results have been limited to samples.

Results and Discussions

The results have been presented in descriptive (sample) statistics, gaps measurements and by inferential statistics along with their interpretations.

Descriptive Statistics

The questions of nominal scale have been summarized applying mode and that of interval scale have been presented with the scores of means and standard deviations (SDs). The study has reported most of the respondents are men (79.2%), oscillated in the age group of 18–25 years (30.2%), married (56.6%), general in caste (53.5%), CA by profession (34%) and mostly having 0–5 years of experience (37.1%).

For expectation-related issues like reporting practices, the average means of items have computed as 3.66 and average SD as 1.31, with highest mean 3.89 and Cronbach alpha ranges from 0.731 to –0.738. The average means of items under role of company auditors 4.02, highest mean 4.13, average SD 1.212 and Cronbach alpha has oscillated between 0.732 and 0.735. For regulatory requirements, the average means of the items have been stood at 3.92, average SD 1.16, highest mean 4.28 and a reversed score item; Cronbach alpha values ranges from 0.733 to 0.751. For IFRSs convergence, the average means of items have calculated as 3.80, average SD 1.201, highest mean 4.09 with a reversed score item; Cronbach alpha scores lie between 0.741 and 0.753.

For perception-related questions under reporting practices, the average means of items have computed as 3.85, average SD 1.20, highest mean 4.03 with a reversed score item; Cronbach alpha scores lie between 0.736 and 0.743. For role of company auditors, the average means have calculated as 3.82, average SD 1.22, highest mean 4.12 with a reversed score item; Cronbach alpha scores lie between 0.737 and 0.747. The average mean for regulatory requirements has computed as 3.96, average SD 1.20, highest mean 4.18 with a reversed score item; Cronbach alpha scores oscillated between 0.742 and 0.747. For IFRSs convergence, the average means of items have calculated as 3.86, average SD 1.13, highest mean 4.18 with two reversed score items; Cronbach alpha scores have been oscillating between 0.735 and 0.745. Tables 2 & 3 have summarized the rationality and underlying assumptions for the chosen statistical tests. These have exclusively been compiled by the authors. The stated tables have only been used for the stated purposes and have not been related to other texts.

Table 2.

Choice of Tests

Tests	Variables						Purposes	Null Hypotheses
	Predictors			Outcomes
	Name	Measurement	No.	Name	Measurement	No.
Spearman’s Rank Correlation	Regulatory Requirements	Interval (Likert Type)	1	Ind AS	Interval (Likert Type)	1	To measure the association’s underlying strength and movements that has been existing between the two parameters which have been assessed at an ordinal scale	H01
Kruskal Wallis Test	Ind AS (Education Levels)	Categorical (Independent Groups)	1	Reporting practices, audit quality and forecasting	Interval (Likert Type)	3	To measure whether there have been any statistically significant differences between two or more groups of a predictor on the ordinal outcomes	H02

Source: The authors.

Table 3.

Assumptions Hold for Selected Tests

Tests	Type	Rationale
Spearman’s Rank Correlation	Non-parametric	Both predictor and the outcome have measured on interval scale, existence of monotonic relations, that is, both the variables have either increased or one has increased and the other has deceased.
Kruskal Wallis Test	Non-parametric	Kruskal Wallis Test has been used in as much the predictor has 5 categorical independent groups and 3 outcomes have been measured on Likert type categorical data. Furthermore, the respondents have divergent educational qualifications.

Source: The authors.

Measurement of Gaps

Mean Expectation–Perception Gaps Analysis

The mean expectation–perception gaps have been summarized in Table 4.

Table 4.

Mean Scores of Expectation Gaps

Basis of Measurements	Expectation (E)		Perception (P)		Mean Expectation Gaps (E-P)	Paired T-test [Sig. (two-tailed)]
Basis of Measurements	Question Nos	Mean Scores	Question Nos	Mean Scores	Mean Expectation Gaps (E-P)	Paired T-test [Sig. (two-tailed)]
Reporting practices	1	3.30	26	3.11	0.19	0.336
	2	3.79	27	3.54	0.25	0.089
	3	3.63	28	3.53	0.10	0.474
	4	3.87	29	3.84	0.03	0.017
	5	3.82	30	3.89	(0.07)	0.430
	6	4.00	31	3.97	0.03	0.422
Role of company auditors	7	4.03	32	3.95	0.08	0.400
	8	4.03	33	3.92	0.11	0.418
	9	4.12	34	4.12	0	0.001
	10	4.13	35	3.40	0.73	0.000
	11	3.88	36	3.74	0.14	0.304
	12	4.03	37	3.64	0.39	0.005
	13	4.01	38	3.92	0.09	0.452
Regulatory requirements	14	4.08	39	4.01	0.07	0.350
	15	4.28	40	3.98	0.30	0.011
	16	4.08	41	4.09	(0.01)	0.876
	17	4.18	42	3.84	0.34	0.012
	18	4.14	43	4.10	0.04	0.453
	19	3.76	44	3.34	0.42	0.016
IFRSs convergence (Ind AS)	20	3.69	45	3.47	0.22	0.132
	21	3.79	46	3.58	0.21	0.111
	22	3.84	47	3.76	0.08	0.456
	23	4.01	48	3.87	0.14	0.279
	24	4.29	49	4.03	0.26	0.489
	25	4.01	50	4.08	(0.07)	0.599

Source: The authors.

It has studied in delve the difference between “Likert scale” and “Likert type scale” as proposed by scholars⁹⁴ and has conceded the applied data collection tool as Likert scale and accordingly has computed the relevant descriptive statistics, that is, mean for measuring the EG, in line with social scientists⁹⁵. Further, the prolonged debate on treating the Likert scale as interval or ordinal has also been duly examined and has inferred for treating the scale as interval, following few scholars^94,96 since the objective of the scale has been confined with measuring the composite score of EG (summated scale), as proposed by Likert himself⁹⁷. The EGs have been measured for 25 paired items (50 individual items) oscillated in four issues divided into 25 items each for expectations and perceptions. Table 4 has reported the mean differences of EG which have been measured by taking the five-point Likert scale (where, 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree and 5 = strongly agree). Under reporting practices, for five out of six pairs, a positive EG has been computed (E > P) which has indicated that the respondents’ expectations have likely been exceeded their perceptions implying the presence of EG; while for one pair, the opposite result has been computed. Role of company auditors have incorporated seven pairs of items of which for six pairs, positive EG has been calculated while for one pair, no such EG has been indicated. Under regulatory requirements, for five out of six pairs, the EG has been computed with positive outcomes and for one pair, results have inferred that respondents’ perceptions have actually outperformed their expectations (E < P), that is, no precedence of EG has likely been reported. Eventually, for IFRSs Convergence (Ind AS), for all six pairs of items, positive EG has been computed. The significant values of paired sample t-test have been reported in Table 5 (Column 7).

Weighted Expectation Gap (WEG) Analysis

Table 5 has computed the weighted expectation–perception gap, that is, the difference in the weighted arithmetic means of item numbers 1 and 26 (respondents’ expectations about the nature of ASs whether it should be principles based or rules based and their perceptions as well) which has been computed as 4. The rationale for choosing weighted mean has been justified as the relative importance of the five-point Likert scores for expectation and perception on 25 paired items have been identified unequally important. That is to say, the scale has five different points for assaying the expectations and perceptions with the assigned numerical values 1–5 which have represented varying expectations and perceptions. Accordingly, the weighted grand total has been divided by the total weighted assigned numbers (15) to get the WAM for both expectations and perceptions. Eventually, the weighted expectation gaps (WEG) have been computed as WAME–WAMp. Adopting the same procedure, the WEG of remaining 24 paired items have chronologically computed with the results as: [1.33, 0.06, 1.67, (1.27), 0.33, 0.54, 1.13, 0, 5.13, 2.93, 3.93, 0.87, 1.34, 1.2, (0.54), 0.47, 0.53, 0.53, 1.07, 1.93, 0.34, 2.67, 0.67 and (2.07)]. The results have reported that WEG for 21 pairs have been computed as positive (the presence of EGs) and that of for 3 pairs negative (no precedence of gap) and for 1 pair, 0 (indifferent). Interestingly, the results have documented that the highest WEG has been computed for the 10th and 35th paired items and it has attempted to assay the expectation and perception of the respondents whether GAAP compliance failure should be reported by auditors or not. On the other hand, for the pair 25th and 50th, the WEG has been computed as most negative (i.e., highest level of non-existence of EG) which has assessed that Ind AS has no significant impact on insider trading activities, and on which the respondents have significantly differed and have perceived reversely.

Table 5.

WEG of Q. 1 and 26

Likert Scale	Expectation (E)				Perception (P)				WEG
	1	2	3	4(3/2)	5	6	7	8(7/6)	9 (4–8)
	Frequency (X1)	Weight (W1)	W1 X1	WAM	Frequency (X2)	Weight (W2)	W2 X2	WAM	9 (4–8)
1	51	1	51	–	41	1	41	–	–
2	10	2	20	–	45	2	90	–	–
3	11	3	33	–	13	3	39	–	–
4	44	4	176	–	35	4	140	–	–
5	43	5	215	–	25	5	125	–	–
Total	159	15	495	33	159	15	435	29	4

Source: The authors.

Paired Sample T-test

To compare the mean of the differences (differed from independent t-test, which compute the difference between the means) of the same respondents’ expectations and perceptions about Indian corporate reporting practices, it has run Paired sample t-test (i.e., two-dependent sample t-test). While running the test, it has controlled the other variables which likely to have influence on the respondents’ expectation–perception, and since the responses have been measured in interval scale, the means of both expectation and perception have been computed for all the 25 pairs.

The descriptive statistics for the first paired sample as presented in Table 6 has computed mean of E as 3.11 and that of for P as 3.30. The last column (SE = s/√N) has been computed as the sample SD divided by the square root of the sample size resulting 0.131 and 0.129 for E and P, respectively. Similarly, for rest of the 24 paired samples, E and P the descriptive statistics have been calculated.

Table 6.

Paired Samples Statistics

Pair	Items	Mean	N	SD	SE Mean
1	IFRSs should be principle-based accounting standard (E)	3.11	159	1.646	0.131
	IFRSs convergence moves from rule based to principle based (P)	3.30	159	1.629	0.129

Source: The authors.

Table 7 has reported in first column the mean difference between E and P on first paired sample which has computed as –1.89. The next column, SD has indicated the value as 0.2463 with standard error 0.195. The test statistic t has been calculated by dividing the mean differences by the SE of differences resulting –0.966. The size of t has compared against known values based on the degrees of freedom (df) and since same sample participants have shared their expectations and perceptions, df has been computed as 158 (n–1). The df has applied to compute the exact probability that a value of t which likely to occur if the H0 has found to be true (i.e., there is no difference between E and P mean values). The probability has been shown in final column labelled as sig. The probability, by default has computed only the two-tailed probability, that is, when no predication was actually been set about the direction of the group differences. The probability for the data has likely been significant (p = 0.036; p < 0.05); and it has likely to conclude that respondents’ expectations have more significant impacts than their perceptions on Indian corporate reporting issues [t (158) = –0.966; p < .05]. Finally, a 95 per cent confidence interval (CI) for mean differences have also been reported which has indicated the boundaries within the true mean values likely to exist, that is, –0.574 and 0.197. Adopting the same procedures, SPSS has produced the results of the remaining 24 paired samples with respective sig. values [0.089. 0.074, 0.017, 0.630, 0.042, 0.040, 0.041, 0.001, 0.000, 0.030, 0.005, 0.045, 0.035, 0.011, 0.876, 0.012, 0.045, 0.016, 0.013, 0.011, 0.045, 0.027, 0.048 and 0.599]. The outcomes have indicated the significant values except for fifth, 16th and 25th paired samples where p > 0.05 and have implied insignificant expectation–perception mean differences. Based on these, it has likely to conclude for most of the paired samples the presence of expectation–perception gaps is there as far as Indian corporate reporting practices are concerned.

Table 7.

Paired Samples Test

	Paired Differences					T	df	Significance (two-tailed)
	Mean	SD	SE of Mean	95% CI of the Difference
	Mean	SD	SE of Mean	Lower	Upper
Pair 1	–0.189	2.463	0.195	–0.574	0.197	–0.966.	158	0.036

Source: The authors.

Inferential Statistics

The different numerical techniques have applied to test the null hypotheses to estimate the likely behaviour of the study–population from which samples have collected.

Rank Correlation

To assess the strength and movement indication of associations between regulatory requirements in the implementation of Ind AS (H01), it has run Edward Spearman’s Rank Correlation.

Table 8 has reported that Spearman’s correlation coefficient, rs, has computed as 0.583, statistically significant (p = 0.096). The statistically significant results have been produced evidence for likely to reject H01, that is, the study probably has to accept the H1 and likely to conclude that regulatory requirements have been significantly influenced in the implementation of Ind AS. The results have also validated the EGs as measured in Table 4 where lower levels of moderate gaps about regulatory requirements have been reported.

Table 8.

Rank Correlations

			Regulatory Requirements	Ind AS Implementation
Spearman’s rho	Regulatory requirements	Correlation coefficient	1.000	0.583
	Regulatory requirements	Sig. (two-tailed)	–	0.096
		N	159	159
	Ind AS implementation	Correlation coefficient	0.583	1.000
	Ind AS implementation	Sig. (two-tailed)	0.096	–
		N	159	159

Source: The authors.

Kruskal Wallis Test

It has run Kruskal Wallis Test to measure whether there has any been significant difference between two or more groups of a predictor, that is, Ind AS (as measured on education levels of respondents) on three ordinal outcomes, namely, reporting practices, audit quality and forecasting, that is, to test H02. Education levels have taken as predictor since the study has attempted to measure the perception-expectation gap of the practitioners during the transition period of Ind AS. The results of the test have been summarized in the following two tables.

From Table 9, it has been validated that the mean rank scores of three outcomes for the same type of predictor say, for example, CA is different 73.98, 75 and 81.31.

Table 9.

Ranks

Outcomes	Education Qualification	N	Mean Rank
Reporting practices	CA	54	73.98
	CMA	16	55.84
	CFA	16	77.03
	CS	18	68.25
	Post Graduate	51	95.33
	PhD	4	127.13
	Total	159
Audit quality	CA	54	75.00
	CMA	16	96.16
	CFA	16	80.25
	CS	18	89.78
	Post Graduate	51	74.34
	PhD	4	110.00
	Total	159
Forecasting	CA	54	81.31
	CMA	16	89.63
	CFA	16	71.00
	CS	18	69.67
	Post Graduate	51	82.09
	PhD	4	79.75
	Total	159

Source: The authors.

Whether the different education levels have different impacts on three outcomes have been measured using the test statistics is reported in Table 10. The results consisting of chi-squared statistic, the degrees of freedom and the statistical significance have been computed. The Chi-Square row have computed results of 17.733, 6.715 and 2.654 for three outcomes, whereas the df have stood at 5 for all these outcomes and the significant values have calculated as 0.003, 0.243 and 0.153, respectively for the outcomes, that is, p > 0.05. The significant results along with different mean rank scores (Table 9) have produced sufficient evidence for likely to reject H02 and it has probably to accept H2 and has concluded that reporting practices, audit quality and forecasting likely significantly improve with the implementation of Ind AS.

Table 10.

Test Statistics^{a, b}

	Reporting Practices	Audit Quality	Forecasting
Chi-Square	17.733	6.715	2.654
df	5	5	5
Asymp. Sig.	0.003	0.243	0.153

Source: The authors.

Notes: (a) Kruskal Wallis Test; (b) grouping variable: education qualification

Conclusion

The study has attempted to measure the practitioners’ EGs about India’s IFRSs convergence. Based on literature review, two research hypotheses and a conceptual model has formed. Adopting cross-sectional study design with online survey strategy, it has collected responses from 159 practitioners. Before the final survey, the questionnaire has been passed through a protocol interviews with three subject experts followed by a pretest with randomly chosen 30 respondents. Based on Cronbach alpha scores, the eventual numbers of items have been fixed at 60, including 10 demographic questions and have been distributed in three sections. Moreover, statistical results of Kaiser-Meyer-Olkin (KMO) and Bartlett’s test of sphericity have indicated the reliability (a good measure) and validity (a right measure) of the questionnaire. The EGs have been measured in four different issues covering 50 items divided into expectation and perception groups containing 25 in each group (i.e., 25 pairs) taking their mean differences, weighted arithmetic mean (WAM) differences as well as by applying dependent paired sample t-test. The results have indicated significant gaps for at least 22 paired samples, rejecting the corresponding null hypotheses that there are no significant expectation–perception gaps. Moreover, significant inferential statistical results have provided evidence likely to reject both the null hypotheses and it has concluded that regulatory requirements probably has effected in the implementation of Ind AS and the latter probably would have effect in improving reporting practices, audit quality and analysts’ forecasting.

The study has acknowledged few limitations before reaching its conclusions. First, in the light of the purpose of the study, it has taken only two hypotheses, selective variables and relatively short duration for carrying out the research. Caution should be taken in generalization as relatively small samples might not be the representative of entire study population. Second, although it has reviewed a good number of academic and professional journals, monographs and expert opinions published in English, literature of other languages has not been consulted. Third, instead of adopting or adapting any established questionnaire, it has developed a self-administered questionnaire for carrying out the survey. Moreover, it has applied five-point Likert scale with an option of “neutral”, which might have attracted the problem of central tendency and instead a four-point Likert scale could be applied to counter the problem⁹⁸. Fourth, in spite of adopting preventive measures, the probability of sampling errors in regards to chosen sampling technique and sample size along with inherent limitations of applied statistical tools might have an impact on overall conclusions⁹⁹. Fifth, the possibility of social desirability bias—a tendency of the respondents to answer as others might perceive to receive^100,101—is likely not to be entirely ruled out. Sixth, the honesty in response is a key issue for any web survey and the current study might be suffered from partial biasness. Seventh, even though men and women respondents have participated, no comparative analysis of their responses have been attempted. Eighth, it has used SPSS-20 for data analysis and its latest versions and other statistical softwares, for example, AMOS, R, Strata have not been applied. Ninth, as practitioners are responsible for implementing IFRSs, the possibility of partial politically acceptable responses still exist as literature validated¹⁰². Finally, instead of individual respondent’s expectation–perception gaps, it has rather measured the collective gaps.

The current study has few practical implications for stakeholders. First, it has measured the expectation–perception gaps of the practitioners about IFRSs convergence during a crucial period of transition to Ind AS (Indian converged version of IFRSs), probably the first of its kind in Indian context. Second, the gaps so measured has indicated at its highest about role of company auditors, and for issues addressing Ind AS it has computed moderately at lower level. Even though the significant inferential statistics have validated that reporting practices, audit quality and forecasting would significantly improve during post-Ind AS implementation era. Third, it has indicated Indian regulatory requirements such as Companies Act, SEBI Act, RBI Act, Income Tax Act and the regulators such as ICAI, SEBI and RBI along with MCA have complied the convergence journey. Moreover, strong political commitment likely has smooth out the process. Fourth, it has validated the desired results from IFRSs convergence, for example, increase in reporting, auditing and forecasting qualities which in turn would attract potential investors from India and abroad in Indian capital and money market instruments. Fifth, foreign analysts and auditors may use the report before taking decisions to work with/for Indian corporates. Finally, the practitioners may use the report for assessing why the sample respondents perceive that EG would be higher in regard to aspects indicated in the study and may assess the standards of Ind AS for reducing those gaps to the extent possible.

Future studies may be attempted in multiple horizons. First, the propriety of IFRSs adoption theories—economic theory of networks and isomorphism—may be tested in IFRSs-convergent countries like India. Moreover, the types of isomorphism—coercive, mimic and normative^103,104—also need to be investigated. Second, the underpinning for convergence—political process theory or the capital need theory—needs to be unearthed. Third, the impact of culture on Ind AS needs to be investigated as pointed out by literature for other countries such as Germany, Australia and Canada¹⁰⁵. Fourth, the IFRSs convergence has motivated the current study and the uniqueness has limited the generalization hence cross-country comparative assessment may be attempted to test the concurrent validity. Fifth, even though reporting and audit quality along with forecasting accuracy in India might be improved, but whether accounting conservatism and other flip sides of Ind AS would offset or not should also be investigated. Sixth, due to parsimony, it has restricted with selective variables and the excluded variables, for example, IFRSs policy choice¹⁰⁶, auditors’ perceptions on fair value¹⁰⁷, impact on taxation¹⁰⁸, and human behaviour as a resistance to change in accounting¹⁰⁹ may be considered in future research endeavours. Seventh, Indian firms using Ind AS and global firms using IFRSs need to be compared in parameters such as inventory valuation, PPE, intangibles and fair valuation techniques to assay the gaps¹¹⁰, if any in such accounting measurements. Eighth, the cause and effect of Ind AS and XBRL on audit fee¹¹¹ needs to be assessed in Indian context. Ninth, EG analysis based on different demographics may be undertaken in future. Tenth, comparative studies may highlight the impacts of specific regulation on the Ind AS compliance status by accessing compliance reports of pre- and post-convergence time line. Finally, future research may assess the convergence effects on financial reporting and capital market as economic consequence like FDI inflow, and cost of equity capital is limited in developing countries¹¹².

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

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