Vol. 3 No. 1 March - April 2020 PHILIPPINE ACADEMY OF MANAGEMENT E-journal ISSN: 2651-7124
RESEARCH ARTICLES
Personality trait and compassion fatigue among nurses assigned 9 in special care units of a tertiary level private hospital in Cebu City Minchu R. Decena and Lauro Cipriano R. Silapan, Jr., University of San Carlos
The application of loss modeling in pricing for group health insurance in the Philippines 22 Soleil G. Baria and Tomas S. Tiu, De La Salle University
ASEAN ICT developments: Current state, challenges, and what they mean for SMEs 37 Raymund B. Habaradas and Ian Benedict R. Mia, De La Salle University
Determinants of mobile money adoption: Evidence from urban Philippines 51 Aristotle Manuel D. Go, Palawan State University
A phenomenological analysis on waste separation behavior 65 and awareness on plastic recovery capability of a barangay in Manila Ranzelle T. Go, Jana D. Josef, Fabienne V. Panelo, Vincent Anthony V. Uy, and Angelique C. Blasa-Cheng, De La Salle University
SPECIAL SECTION COVID-19 Reflections: Thoughts on Managing and Organizing in Times of Crises
''Diskarte' in times of crises 82 Raymund B. Habaradas, De La Salle University
The search for “good” leaders during COVID-19: 84 Reflections on how value systems frame actions during a crisis Eula Bianca Villar, Asian Institute of Management
COVID-19: Lessons from a pandemic 90 Armando J. Aguado, Mapúa University
Philippine Academy of Management e-Journal
Volume 3 Number 1 March – April 2020
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The Philippine Academy of Management e-Journal is an online and open-access peer-reviewed journal that targets a twice-a-year release. It is indexed at the Andrew Gonzalez Philippine Citation Index. As a not-for-profit publication, it does not charge readers access fees nor does it charge authors publication fees. It is supported by the funds generated by PAOM from its membership fees.
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PHILIPPINE ACADEMY OF MANAGEMENT E-JOURNAL VOL. 3 NO. 1
Editorial Board
Dr. Emilina D. Sarreal Editor in Chief De La Salle University
Dr. Raymund B. Habaradas Managing Editor De La Salle University
Advisory Editorial Board
Dr. Edgar Allan G. Castro Dr. Ma. Regina M. Hechanova Editorial Board Member Editorial Board Member De La Salle – Lipa Ateneo de Manila University
Dr. Dinah Pura T. Depositario Dr. Ricardo A. Lim Editorial Board Member Editorial Board Member University of the Philippines Los Baños Asian Institute of Management
Dr. Louis A. Divinagracia Dr. Challoner A. Matero Editorial Board Member Editorial Board Member De La Salle University University of San Carlos
Dr. Divina M. Edralin Dr. Maria Andrea L. Santiago Editorial Board Member Editorial Board Member San Beda University iAcademy and De La Salle University Dr. Benito L. Teehankee Dr. Brian C. Gozun Editorial Board Member Editorial Board Member De La Salle University De La Salle University
Mr. Ian Benedict R. Mia Editorial Assistant and Webmaster Philippine Academy of Management e-Journal
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Editors’ Note
Just like you, we were caught unawares by the rapid spread of the COVID-19 virus, as well as by the disruption caused by the enhanced community quarantine (ECQ) in our lives. We commiserate with those who have lost friends and loved ones due to the pandemic, pray for those recovering from the infection, and thank those manning the frontlines (i.e. health care workers, retail workers, sanitation workers, security personnel, and public servants) to ensure that we have access to essential goods and services during the lockdown.
Thanks to information and communication technology (ICT), we too continued to work in our own homes to put this issue together. This would not have been possible without the cooperation of our authors and reviewers, who generously and patiently worked on the manuscripts until these were finally accepted for publication. We are, therefore, pleased to present the fourth issue of the Philippine Academy of Management (PAOM) e-Journal, which contains the work of business and management scholars from three different universities, namely: De La Salle University, Palawan State University, and the University of San Carlos.
It is either providential or coincidental that we have two articles that are health-related, given that we are currently facing a major health crisis. The article of Minchu Decena and Lauro Silapan examined links between personality trait and compassion fatigue among nurses assigned in special care units of a tertiary level private hospital in Cebu City, while the article of Soleil Baria and Tommy Tiu looked into the application of loss modeling in pricing for group health insurance in the Philippines.
Two articles deal with technology adoption, which has become crucial for us to adjust to the so-called “new normal”, triggered by the present crisis, and characterized by new ways of doing business and going about our daily lives. Raymund Habaradas and Ian Benedict Mia present in broad strokes the progress of ASEAN Member States in formulating their ICT policies and building their ICT infrastructure, which are expected to radically improve public service delivery, reform the educational sector, and create new business models. Aristotle Go, on the other hand, talks about the determinants of mobile money adoption based on some evidence from urban Philippines.
The issue includes also includes an article on the perception of residents of a particular barangay in Metro Manila about waste separation, written by Ranzelle Go, Jana Josef, Fabienne Renee Panelo, Vincent Anthony Uy, and Angelique Blasa-Cheng; and another that looks into the influence of personality traits on service quality experiences by the tourism and hospitality students as guests in a resort, written by Virgilia Arispe.
In this issue, we included a special section titled “COVID-19 Reflections: Thoughts on Management and Organizing in Times of Crises”. Our managing editor poses questions on why pro- active action and resourcefulness (or ‘diskarte’) “seem to be frowned upon by the powers-that-be in this time of crisis”. Eula Bianca Villar provides some answers as she elaborates on how leaders’ value systems frame their actions during crisis situations. Finally, Armando Aguado looks ahead by discussing the prospects of work-from-home arrangements and online learning post-COVID-19. He also makes a case for building up the capability of companies to undertake crisis management through business continuity plans.
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PHILIPPINE ACADEMY OF MANAGEMENT E-JOURNAL VOL. 3 NO. 1
To conclude, we are pleased to announce that our journal has finally been recognized by the Andrew Gonzalez Philippine Citation Index, which assesses academic journals based on journal leadership and management, peer review and quality of published articles, and timeliness, frequency, and diversity of publications. This means that we have to step up our game so that we will be able to meet all the above-mentioned criteria where the AGPCI reassesses our worthiness in two years’ time. We have, therefore, expanded our pool of reviewers to speed up the review process, which is currently serving as a bottleneck. We have also opened up the journal to manuscripts outside of those submitted to the National Business and Management Conference (NBMC), which have been the primary source of published articles in our past three issues. In the meantime, we have established an efficient tracking system, which has allowed us to monitor the progress of several dozen manuscripts currently in the pipeline. We have approved several manuscripts for the September 2020 issue, and are waiting for a couple more to meet our minimum number of articles for one issue. We are hoping that in the next few weeks and months, we will be receiving a steady stream of submissions, even as we expect a new set of manuscripts after the 8th NBMC, which is tentatively set in November 2020.
EMILINA D. SARREAL, DBA Editor in Chief, PAOM e-Journal
RAYMUND B. HABARADAS, DBA Managing Editor, PAOM e-Journal
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PHILIPPINE ACADEMY OF MANAGEMENT E-JOURNAL VOL. 3 NO. 1
TABLE OF CONTENTS
Editorial Board 3
Editors’ Note 4
RESEARCH ARTICLES
Personality trait and compassion fatigue among nurses 9 assigned in special care units of a tertiary level private hospital in Cebu City Minchu R. Decena and Lauro Cipriano R. Silapan, Jr. University of San Carlos
The application of loss modeling in pricing for 22 group health insurance in the Philippines Soleil G. Baria and Tomas S. Tiu De La Salle University
ASEAN ICT developments: 37 Current state, challenges, and what they mean for SMEs Raymund B. Habaradas and Ian Benedict R. Mia De La Salle University
Determinants of mobile money adoption: 51 Evidence from urban Philippines Aristotle Manuel D. Go Palawan State University
A phenomenological analysis on waste separation 65 behavior and awareness on plastic recovery capability of a barangay in Manila Ranzelle T. Go, Jana D. Josef, Fabienne V. Panelo, Vincent Anthony V. Uy, and Angelique C. Blasa-Cheng De La Salle University
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SPECIAL SECTION
COVID-19 Reflections: Thoughts on Managing and Organizing in Times of Crises
‘Diskarte’ in times of crises 82 Raymund B. Habaradas De La Salle University
The search for “good” leaders during COVID-19: 84 Reflections on how value systems frame actions during a crisis Eula Bianca Villar Asian Institute of Management
COVID-19: Lessons from a pandemic 90 Armando J. Aguado Mapúa University
Author Guidelines 94
The Contributors 96
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PHILIPPINE ACADEMY OF MANAGEMENT E-JOURNAL VOL. 3 NO. 1
Personality trait and compassion fatigue among nurses assigned in special care units of a tertiary level private hospital in Cebu City
Minchu R. Decena and Lauro Cipriano R. Silapan, Jr. University of San Carlos [email protected]
Abstract
The attainment of good health and well-being is dependent on the existence of a robust and thriving health care industry. Nurses play a vital role in this industry in giving patient care. The 35- 40% attrition rate among nurses experienced by private hospitals at present threatens organizational sustainability. Extant literature mentions the influence of personality traits on stress and burnout among others as reasons of nurse turnover. This prompted the researchers to examine the personality traits and level of compassion fatigue among nurses of a tertiary level private hospital in Cebu City. In this study, burnout (BO) and secondary traumatic stress (STS) define compassion fatigue.
This descriptive, correlational, and cross-sectional research surveyed 123 staff nurses assigned in the special care units. However, there were only 105 returned questionnaires with complete data. The data on personality traits were collected using the Big Five Personality Test scale (Socha, Cooper, & McCord, 2010). The ProQOL version 5 scale of Stamn (2010) was used to collect data on the level of BO and STS. Data were analyzed using SPSS version 25.
Results revealed that respondents had average levels of the traits Openness, Extroversion and Neuroticism and high levels of the traits Conscientiousness and Agreeableness. Average levels of BO and STS were also noted. Moreover, results showed significant negative relationships between BO and Conscientiousness, Extroversion, Agreeableness and Neuroticism while the traits Conscientiousness, Agreeableness and Neuroticism had significant negative correlation with STS. Thus, the higher the levels of the Big 5 Personality traits, the lower is the BO and STS levels.
It can be concluded that nurses with average to high levels of the traits Openness, Conscientiousness, Extroversion and Agreeableness can cope very well with compassion fatigue. Low level of Neuroticism trait is ideal in the healthcare industry. Although the study showed average BO and STS levels, it is prudent to keep this at low levels. Some of the identified interventions that need to be implemented to keep BO at low levels include the purchase of devices that decrease physical exertion in performing nursing tasks, automation of identified standard processes, conduct of multi-disciplinary meetings and self-awareness, and effective communication trainings. To reduce STS levels further, the hospital may provide training for nurses to cope with death related grief, implement buddy system, and provide opportunities for cross-functional team bonding activities.
Key Words: big five personality traits; compassion fatigue; burnout; secondary traumatic stress; special care unit nurses
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Introduction
The sustainable development goal 2030 spearheaded by the United Nations has considered the attainment of quality of health standards and promotion of the welfare for young and old people as objective number 3. This puts focus on the Philippine healthcare industry as an important stakeholder in this endeavor where nurses play an important role in the healing process by providing direct patient care (George & Reyes, 2017). The inability to hire and to adequately address hospital staffing levels together with the continued migration and turnover of nurses impacts patient safety and hospital operational sustainability.
Perrin, Hagopian, Sales and Huang (2007) described the significant difference between government and private hospitals nursing-staffing situation in the Philippines and noted a 17% turnover rate of staff nurses in government hospitals in 2004. In 2018, HR practitioners of private hospitals shared that a turnover rate of 35-40% for staff nurses is now the new normal. Filipino nurses considered low wages and below standard benefit packages, lack of personal development opportunities, workload with high nurse to patient ratios and poor nursing law enforcement as factors for nurse migration (Labrague, McEnroe-Petitte, Tsaras, Cruz, Colet, & Gloe, 2018). This is validated by the study of George et al. (2017) which noted a nurse patient ratio of 1:30 in government run hospitals in the Philippines compared to the ideal ratio of 1:12.
Schaufeli (2017) posited that increase in personal resources and presence of stimulating leadership environment, the incidence of BO decrease and increase in work engagement is obtained. The exposure and interaction of healthcare workers with terminally ill patients is a common “job demand” which can lead to the phenomenon called compassion fatigue. Compassion fatigue is a reaction to stress experienced by healthcare professionals resulting to the decline in the capacity to care for others due to the nature of one’s work. Nurses experience impairment in their physical, social, emotional and spiritual health due to stress brought about by the high volume of interaction with complex patients on a daily basis (Sinclair, Raffin-Bouchal, Venturato, & Mijovic- Kondejewski, 2017). The correct matching of the right person with the appropriate personality, knowledge, and skills to the right position (Afsar, Badir & Khan, 2015) is a proactive strategy to counter the effects of compassion fatigue.
The hypothetical conceptual model of professional quality of life of Yu, Jiang and Shen (2016) was utilized to frame the variables of the study, namely, big five personality traits and compassion fatigue elements, BO and STS. The framework of Patterson, Grenny, Maxfield, McMillan and Switzler (2008) called Six Sources of Influence Model which identified motivation and ability in assessing personal, social and structural domains was the basis in drafting recommended intervention programs for the organization.
This research conducted on a tertiary level private hospital in Cebu City, aimed to find out the personality traits and compassion fatigue level among nurses assigned in the special care units. Specifically, the researchers aimed to address the following research objectives: 1) determine the personality profile of nurses, 2) determine the level of compassion fatigue of nurses, and 3) determine the relationship between personality traits and compassion fatigue of nurses. The outcomes of the study were recommendations for the desired personality profile of nurses to be assigned in the special care unit and intervention programs to address compassion fatigue.
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PHILIPPINE ACADEMY OF MANAGEMENT E-JOURNAL VOL. 3 NO. 1
Review of Related Literature
Compassion Fatigue
Joinson (as cited in Boyle, 2011) defined compassion fatigue as the diminished ability of health providers to attend to and empathize for others needing of the care. This is brought about by constant exposure to negative and traumatic experiences. Figley (2002) believed that there is cost to being compassionate and emphatic which resulted to the reduced capacity in bearing the suffering of others. Sinclair et al. (2017) posed concerns on the solid operational foundation of the concept of compassion fatigue due to unavailability of standard measurement tool. Diagnosis was further complicated with the presence of more than 40 physical, behavioral, spiritual and psychological symptoms.
Stamm and Figley co-developed a conceptual model and tool to measure compassion fatigue called Professional Quality of Life or ProQOL (Sheppard, 2015). Stamm (2010) modified the model and defined compassion fatigue as having two (2) elements: burnout (BO) and secondary traumatic stress (STS). BO was associated with the emotion hopelessness, senselessness, and of being ineffective with what one is trying to accomplish. These resulted from high level of work assignment without enough emotional and psychological support (Stamm, 2010). STS was associated with work related secondary exposure to extremely or traumatic conditions/events experienced by those who provide care for others with sustained physical or emotional injuries (Stamm, 2010).
Stamm (2005) claimed that the ProQOL (the third revision of Compassion Satisfation/Fatigue Self-Test) was a good measurement tool for compassion fatigue and issues raised about the challenge in separating the element of BO from STS were eliminated. Galiana, Arena, Oliver, Sanso and Benito (2017) concluded that STS and BO were psychometrically different constructs. Stamm (2010) further asserted that a direct measure of compassion fatigue was unavailable and that scores should be treated as stand-alone specific numbers. Efforts to create a composite indicator to date had been made but no satisfactory arrangement had been discovered (Stamm, 2010).
Personality Traits and the Big Five Personality Model
John and Srivastava (1999) stated various personality assessment tools using the same names but not measuring similar constructs or scales led to the difficulty in making a unified personality taxonomy acceptable for all researchers. They further posited that the emergence of the big five broad dimensions of personality namely, Extraversion, Agreeableness, Conscientiousness, Neuroticism and Openness, established a common framework providing the broadest level of distinct and specific personality characteristics. Gosling, Rentflow, and Swann, Jr. (2003) described the Big Five framework as a model with five broad bipolar factors (i.e., Extroversion vs Introversion) broken into more specific traits (i.e., talkative and outgoing). The availability of many instruments to test personality traits and the difficulty to pin down universal meanings to the different trait dimensions showed the absence of an ideal standard instrument (John and Srivastava, 1999).
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Barrick and Mount (1991) observed common traits used to describe each factor despite the different names attached to each factor. Extraversion or Extroversion, was associated with the tendency to be sociable, gregarious and assertive while Emotional Stability or Neuroticism was associated with the traits of being anxious, emotional, and depressed. Agreeableness was associated with the traits of being courteous, flexible, and tolerant. Conscientiousness was associated with the traits of dependability, responsible, and organized while Openness to experience was associated with the traits of being curious, artistic, and intelligent.
The Big Five Personality Traits and Compassion Fatigue
The review of available literature on the relationship of the Big Five Personality traits and compassion fatigue is limited. The study of O’Mahony, Ziadni, Hoerger, Levine, Baron, and Gerhart (2017) investigated the relationship of personality factors and years of work experience and level of compassion fatigue of palliative care clinicians in Midwest Academic Medical Center. Results revealed that long tenured palliative clinicians had lower BO level and higher level of satisfaction contrary to the belief that the longer an individual was exposed to traumatic conditions the higher the BO level. The results further showed that high score in agreeableness produced high level of satisfaction and low level of BO but did not relate to STS. High neuroticism score was strongly associated to STS and BO.
Yu, Jiang and Shen (2016) used ProQOL in investigating the factors that lead to the incidence of compassion fatigue, BO, and compassion satisfaction among Chinese oncology using the Chinese version of the Big Five Personality Inventory. The investigation showed that higher levels of compassion fatigue and BO were observed in tenured nursing practitioners working in secondary hospitals. Trainings, positive, and empathetic work environment acted as organizational support thus decreasing the incidence of compassion fatigue and BO. Proper perspective taking increased compassion satisfaction and the traits of openness and conscientiousness were directly correlated with compassion satisfaction. Neuroticism was directly correlated with compassion fatigue (Yu et al., 2016).
Zellars, Perrewe, and Hochwarter (2000) conducted a study on nurses in a large hospital in a US metropolitan city, to test which dimensions of the big five personality traits had an effect on the 3 components of BO which were emotional exhaustion, depersonalization, and diminished personal accomplishment. Result showed that neuroticism failed to predict depersonalization and personal accomplishment but had significant influence on levels of emotional exhaustion. Zellars et al. (2000) further stated that higher levels of Agreeableness trait showed a reduced tendency to depersonalize a patient. Extraversion was positively associated with less depersonalization and in perceiving fewer personal accomplishments. Openness had marginal significance with depersonalization and warranted further study but appeared to allow individuals to perceive greater personal accomplishments. What was interesting to note was the failure of Conscientiousness to predict any of the BO components.
Chen, Tsai, Lu, Lin, Lu, and Wang (2018) posited that the personality traits of Agreeableness, Extraversion, Conscientiousness, and involvement in outdoor activities were determinants of compassion satisfaction. Chen et al., (2018) further highlighted that the personality traits of Conscientiousness, Agreeableness, and Emotional Stability were negatively associated with
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PHILIPPINE ACADEMY OF MANAGEMENT E-JOURNAL VOL. 3 NO. 1 compassion fatigue. Married pediatric nurses with high Emotional Stability score had lower compassion fatigue scores compared to single pediatric nurses with same Emotional Stability scores. Risk factors in predicting compassion fatigue were Emotional Stability and marital status. In the same study, it was noted that contrary to other studies, pediatric nurses had level of compassion fatigue attributed to the presence of supportive workplace culture. Theoretical and Conceptual Framework
Chen et al., (2018) noted the dearth of studies on the relationship of personality traits with BO and STS. Among the studies that investigated this relationship include that of Armon, Shirom, and Melamed (2012) which showed that Neuroticism and Conscientiousness were significant predictors of BO. Another study showed a negative relationship between Agreeableness and BO and Neuroticism posted strong correlation with BO and STS (O’Mahony et al., 2017).
The modified ProQOL model of Stamm (2010) posited that BO and STS are elements of compassion fatigue. Support for this conceptualization were found in the studies of Devilly et al., 2009 as cited in Galiana et al.( 2017) and Adams, Boscarino, and Figley (2006) which found construct validity in STS and BO.
The conceptual framework used in the current study incorporated the hypothetical model of Professional Quality of Life of Yu et al., (2016) and Stamm’s (2010) conceptualization of Compassion Fatigue. These two were utilized to illustrate the relationship of personality traits and compassion fatigue among staff nurses in 6 special care units of a tertiary level private hospital in Cebu City (Figure1).
Figure 1. Personality Trait - Compassion Fatigue Impact Model (adapted from Yu, Jiang, and Shen, 2016 and Stamm 2010)
The results of the research were used as bases for recommending a personality profile appropriate for nurses to be assigned in the special care units and for the creation of human resource intervention programs designed to mitigate the impact of compassion fatigue.
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Research Methodology
The current study adopted a descriptive, correlational, and cross-sectional research design to investigate the relationship between personality traits and compassion fatigue among nurses assigned in the special care units of a tertiary level private hospital in Cebu City. The Big Five Personality Test questionnaire and ProQOL version 5 were utilized in this research while quantitative data were analyzed using Statistical Package for Social Science (SPSS) version 25 software
Research Environment and Respondents
The respondents (i.e., the number of respondents follows the unit enclosed in parenthesis) of this study were Philippine licensed registered nurses assigned in the identified specialized care units, namely, Cardiovascular Critical Care Unit (CCU - 11), Neuro Critical Care Unit (NCCU - 22), Intensive Care Unit (ICU - 27), Intermediate Care Unit (INT - 21), Neonatal Intensive Care Unit (NICU - 18) and Pediatric Intensive Care Unit (PICU - =6). Nurses assigned in these units were exposed daily to patients with critical ailments needing differing levels of acuity of care. Six months regular of Patient Care Unit (PCU) experience was required prior to special care unit assignment to ensure adjustment and familiarization with complex patient care processes and protocols making these units an ideal environment in which to measure compassion fatigue.
Research Instruments and Procedures
The current research used M5-50 BFP Test (M5-50) available through the IPIP website. Goldberg et al.(1999) (as cited in Socha et al., 2010) made the test material available at no cost online and requiring no necessary permission on its use. Socha et al., (2010) through CFA research methodology provided corroborative data on the construct validity and reliability of the M5-50 test tool. Socha et al., (2010) further stated that M5-50 tool was a viable measure of the big five factor model while Warlick, Ingram, Vuyk and Multon (2019) claimed that M5-50 tool was able to capture the distinct traits in each domain.
Socha et al., (2010) provided reliability values (Cronbach alpha) for the traits: Extroversion = .863, Agreeableness = .759, Conscientiousness = .849, Neuroticism =.864 and Openness =.778. The questionnaire contained 50 items asking the respondents to express their degree of agreement or disagreement to each item using the following rating scale: 1-disagree; 2- slightly disagree; 3- neutral; 4- slightly agree, and 5- agree. The rating procedure yielded scores of between 0 to 40. Each personality trait has 10 items.
The M5-50 descriptors were as follows: Extroversion referred to the tendency to seek fulfillment from outside sources. High scores indicated a person’s tendency to be very sociable while low scorers had the inclination to work alone. Agreeableness reflected the trait of adjusting one’s behavior to suit others. High scores manifested one’s propensity to be likable and being polite to others while low scores indicated one’s propensity to express oneself the way it is. Conscientiousness suggested the tendency to be honest and hardworking and high scores of this trait suggested the preference to follow rules while low scorers showed the inclination to be haphazard. Neuroticism in this tool was defined as the tendency of being emotional. Openness to experience showed the
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PHILIPPINE ACADEMY OF MANAGEMENT E-JOURNAL VOL. 3 NO. 1 tendency to seek new experience and intellectual pursuits. High scorers indicated the predisposition to dream a lot while low scorers seemed to be down to earth.
The Professional Quality of Life (ProQOL) version 5 (Stamn, 2010), a 30-item questionnaire, was used to determine the scores of BO and STS. Rating was according to frequency of occurrence of the experience within the past 30 days. Ratings were 1- Never; 2-Rarely; 3- Sometimes; 4- Often and 5- Very Often. Stamm (2010) stipulated the average score of BO (S. D. = 10) as 50 and a 0.75 alpha scale reliability. STS (S.D. = 10) had an average score of 50 and a scale reliability of 0.758. Big Five Personality Test scores were interpreted as 0-7 (very low), 8-15 (low), 16-23 (average), 24- 31 (high) and 32-40 (very high). Both BO and STS used the sum of the questions per element with scores 22 or less (low), between 23 and 41 (average) and 42 or more (high).
The Institutional Review Board of the tertiary level private hospital granted approval for the conduct of the study. A pretest was conducted with staff nurses assigned in the renal unit and yielded reliability values of (Cronbach alpha) M5-50 = .845 and Compassion Fatigue = .758. The survey questionnaires were given to all staff nurses (N=123) assigned in the special care units. The retrieval rate was 85% (N=105). Questionnaires did not require respondents to provide their names to maintain anonymity. The nurses were given two weeks to give them ample time to answer. Scoring and interpretation were handled by the researchers. All data collected were treated with confidentiality and in compliance with the Data Privacy Act.
Findings and Interpretation of Data
Demographics of Target Participants
The research respondents were - 123 staff nurses of the hospital. Of this number, only 105 completely filled out questionnaires were useable and yielded a participation rate of 85% (N = 105). Results revealed that 71% of the workforce assigned in the special care units were female (N = 75), 86% single (N = 90), 90% between the ages of 21 to 35 (N = 95) and 47% had tenure of 1 to 2 years (N = 49). Results of the demographic factors tenure and age were a reflection of the reality that upon completion of employment contracts, nurses resign for opportunities overseas leaving behind nurses with minimal nursing work experience. Studies on intention to leave (Labrague et al., 2018; Liang, Tang, Wang, Lin, and & Yu, 2016) identified new and younger nurses to be highly predisposed to leaving the organization, due to issues related to low salaries, opportunities for advancement, and increase in workload.
Personality Traits of Nurses in the Different Special Care Units
Results of the study revealed an overall mean score for the openness trait of 23.49 (S.D. = 3.69). The mean scores for nurses in CCU, ICU, and NCCU were 25.00, 24.41, and 24.05, respectively. The average to high level of Openness indicates the ability of nurses to welcome difficult cases and additional patient load. This behavioral pattern allows the nurses to handle varying needs and complex demands of the patients’ significant others.
The high level of the Conscientiousness trait was noted (M = 26.8, S.D. = 5.03). This trait proves to be very useful in enabling nurses to observe patient care protocols despite long duty hours.
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Extroversion was at average level with a mean score of 18.46 (S.D. = 5.77). Among the nurses assigned to various units, only NICU nurses showed low level of Extroversion (M = 15.44, S.D. = 6.46). Low level of the trait extroversion would present a tendency to be reticent in communicating and dealing with patients and significant others.
High mean score of 26.43 (S.D. = 4.61) denoted high level of Agreeableness in the different special care units. A high score facilitates smooth working relationship among nurses in multidisciplinary teams. Neuroticism was seen at an average level (M = 18.08, S.D. = 5.81). A low score (indicating emotional stability) for this trait is desirable. This allows nurses during stressful situations to calmly perform designated tasks and roles as taught in numerous trainings. PICU posted the lowest level of Neuroticism at a mean score of 14.17 (S.D. = 2.93) which indicated high level of emotionally stability compared to nurses in the other units.
Levels of Compassion Fatigue of Nurses in the Different Special Care Units
Average level of BO and STS were noted in nurses deployed in these areas. BO yielded a mean score of 25.93 (S.D. = 4.84) while STS showed a mean score 25.17 (S.D. = 5.82). The 12 hour shifts due to unfilled staff nurse headcount, increased workload due to increasing nurse to patient ratio and sometimes unsupportive multidisciplinary team were identified causes of BO. Constant exposure to terminally ill patients admitted in the special care units and dealing with demanding significant others raised the incidence of STS. The 90% occupancy rate with reduced number of nurses resulted to more load and extended work hours for nurses explained the level of BO. Long work hours that extend the exposure of staff nurses to traumatic experiences explained high level of STS.
PICU posted the lowest level of BO with a mean score of 22.50 (S.D. = 1.87) and STS with a mean score of 21.50 (S.D. = 2.81), compared to the other units. This was attributed to fewer number of patients to take care of and fewer significant others to deal with.
Sprang, Clark, and Whitt-Woosley (2014) posited that long working hours, length of the duration of assignment and number of caseloads involving trauma patients increase the incidence of STS and BO while George et al. (2017) stated that BO among nurses were common occurrence due to increase in workload which required physical exertions and continued patient monitoring.
Relationship of Personality Traits and Compassion Fatigue of Nurses
Table 1 shows the over-all relationship between the different personality traits and the elements of compassion fatigue, namely, BO, and STS. BO had negative relationship with Conscientiousness (r = -.359, p = 0.000), Extroversion (r = -.391, p = 0.000), Agreeableness (r = - .429, p = 0.000), and Neuroticism (r = -.453, p = 0.000). This implies that nurses with high levels of Conscientiousness, Extroversion, Agreeableness, and Emotional Stability (or low level of neuroticism) tend to exhibit lower levels of burnout and stress. Similarly, STS correlated negatively with Conscientiousness (r = -.357, p = 0.000), Agreeableness (r = -.281, p = 0.004), and Neuroticism (r = -.467, p = 0.000). The more conscientious, agreeable, and emotionally stable (or less neurotic) the nurses are, the lesser is the effect of STS on them.
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Table 1 Relationship of Personality Traits of Nurses and Compassion Fatigue
Personality Burnout Secondary Trait Traumatic Stress Openness Pearson Correlation -0.159 -0.146 Conscientiousness Pearson Correlation -.359** -.357** Extraversion Pearson Correlation -.391** -0.074 Agreeableness Pearson Correlation -.429** -.281** Neuroticism Pearson Correlation -.453** -.467** Note: **Correlation is significant at the 0.01 level (2-tailed). N= 105. *Correlation is significant at the 0.05 level (2-tailed). N = 105.
Table 2 shows data of the relationship of the traits and compassion fatigue in the different special care units. In the case of CCU, BO showed moderately strong negative correlation with Agreeableness (r = -.632, p = 0.037) while STS likewise had a moderately strong negative relationship with Neuroticism (r = -.683, p = 0.020). The more agreeable and emotionally stable (low neuroticism level) are the nurses, the lower are the burnout and stress levels.
The findings for nurses in the ICU, where there was a steady inflow of patients already admitted and waiting to be admitted, reflected low negative correlation between BO and extroversion (r = -.406, p = 0.036), moderate negative correlation with agreeableness (r = -.511, p = 0.006) and neuroticism (r = -.555, p = 0.003). STS posed a significant moderately strong negative relationship with Neuroticism (r = -.546, p = 0.003).
A particular focus of interest is INT (i.e., as a step-down unit for ICU), which ranks next to ICU with the fewest number of staff nurses to oversee the 24/7 operations of the unit. This unit oversees long staying terminally ill patients with Allow Natural Death directive from significant others and other patients who were dependent on life support machines. This observation is manifested in the results showing an inverse correlation between BO and Extroversion (r = -.553, p = 0.019) and STS with Conscientiousness (r = -.508, p = 0.019) and Neuroticism (r = -.641, p = 0.002). This implies that despite such work pressures, certain personality factors seem to have enabled nurses to maintain their composure and handle stress and burnout.
Nurses in the NCCU are exposed to intubated, post-operative neuro cases. Results indicated a moderately strong negative relationship between BO (r = -.739, p = 0.000) as well as STS (r = - .622, p = 0.002) and Conscientiousness. Nurses who have high levels of Conscientiousness tend to display lower levels of burnout and stress. Significant negative relationships between BO and Agreeableness (r = -.530, p = 0.011) and Neuroticism (r = -.484, p = 0.023) were also noted while STS negatively correlated with Agreeableness (r =-.503, p = 0.017).
Results for NICU, which caters to the critical needs of patients aged 0 to 28 days, showed negative relationships between BO and Openness (r =-.518, p = 0.028), Conscientiousness (r = -.501, p = 0.034), Extroversion (r = -.754, p = 0.000), and Neuroticism (r = -.596, p = 0.009) and a negative
17 | P a g e www.paomassociation.wordpress.com relationship between STS and Openness (r = -.604, p = 0.008) and Neuroticism (r = -.491, p = 0.039). The higher are the levels of these personality traits, the lower is burnout and stress.
Results for the PICU unit, whose mandate is to take in critically ill patients with ages 0 to 18 years old displayed a very strong positive correlation between STS and Conscientiousness (r = .956, p = 0.003). The higher the level of Conscientiousness, the higher the level of STS experienced by staff nurses. This was attributed to the level of care needed by young patients, dependent on the technical acumen of the nurses. Significant negative correlation between STS and Extroversion (r = -.939, p = 0.006) and Neuroticism (r = -.912, p = 0.011) were noted.
Data derived from the study were similar to the study of Chen et al., (2018) conducted on pediatric nurses which identified the personality traits Conscientiousness (r = -0.32, p < 0.001), Agreeableness (r = -0.27, p < 0.001), and emotional stability (r = -0.44, p < 0.001) to be negatively associated with compassion fatigue. Chen et. al. (2018) further stated that high level of Conscientiousness, Agreeableness and Emotional Stability led to lower level of compassion fatigue. Ang, Dhaliwal, Ayre, Uthaman, Fong, Tien, Zhou, and Della (2016) in a study on Singapore tertiary hospital nurses revealed that high levels of Extraversion, Openness, Agreeableness and Conscientiousness provided protective effect leading to low level of BO.
Table 2 Relationship of Personality Traits of Nurses in Special Care Units and Compassion Fatigue
Special Care Unit Area O C E A N CCU Burnout Correlation -0.100 -0.499 -0.246 -.632* -0.571 N=11 STS Correlation 0.213 -0.143 -0.025 -0.344 -.683 * ICU Burnout Correlation -0.151 -0.194 -.406* -.511** -.555** ** N=27 STS Correlation 0.059 -0.343 0.005 -0.206 -.546 INT Burnout Correlation -0.140 -0.380 -.553** -0.389 -0.431 N=21 STS Correlation -0.385 -.508 * 0.133 -0.006 -.641 ** NCCU Burnout Correlation 0.140 -.739** 0.027 -.530* -.484* ** * N=22 STS Correlation 0.134 -.622 0.073 -.503 -0.165 NICU Burnout Correlation -.518* -.501* -.754** -0.355 -.596** ** * N=18 STS Correlation -.604 -0.457 -0.424 -0.436 -.491 PICU Burnout Correlation -0.552 0.665 -0.660 -0.087 -0.712 N=6 STS Correlation 0.367 .956** -.939** -0.562 -.912* Note: **Correlation is significant at the 0.01 level (2-tailed); n = 105. *Correlation is significant at the 0.05 level (2-tailed); n = 105.
Conclusion
Nurses with average to high levels of Openness, Conscientiousness, Extroversion and Agreeableness as well as low to average level of Neuroticism (i.e., moderate level of emotional stability) can cope very well with compassion fatigue. Although the study showed average BO and STS levels, it would be prudent to keep this at low levels. Factors such as level of technical competency of the nurses and number of patients being attended to, formed part of the limitation of the study. Generalizability of the result of the study is not applicable beyond this small sample.
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Recommendations
The personality profile appropriate for nurses for the specific work environment of the special care units of the hospital requires average to high level of the personality traits Openness, Conscientiousness, Extraversion, Agreeableness and low to average level of Neuroticism to address BO and STS levels.
The six sources of influence of Patterson et al. (2008) served as the framework for the recommended intervention programs to bring about sustainable change. New interventions to counter the effects of BO and STS were recommended for implementation to address personal domain. The first is the inclusion of the Big 5 Personality factor in the recruitment process. Carless (2009) posited that psychological test results together with the interview result are predictors in the selection process. The second is the conduct of supplementary trainings which covers effective communication, dealing with customers, coping skills to alleviate death related grief and psychological adjustment (Yu et al., 2016).
The implementation of multi-disciplinary discussions with doctors, residents and nurses on patient care protocol and implementation of the buddy system provide social domain interventions meant to address BO and STS. Chen et al., (2018) has stated that positive work environment positively mitigates the negative impact of burnout, compassion fatigue, absenteeism, and attrition of nurses. The acquisition of devices to lessen physical exertion (George et al., 2017) and automation of records keeping and charting (Sprang et al., 2014) were recommended structural domain interventions to address BO and STS.
Future studies with the intent to replicate this in other patient care units in both private and public tertiary level hospitals can be done. This will provide a better understanding on the relationship of compassion fatigue and personality traits and recommend interventions that will mitigate incidence of BO and STS of staff nurses.
Acknowledgments
The researchers are grateful to the nurse respondents and nursing leaders who participated and shared their valuable time, support, knowledge and information relevant to this study as well as USC for aiding in improving this paper.
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Perrin, M. E., Hagopian, A., Sales, A. & Huang, B. (2007). Nurse migration and its implications for Philippine hospitals. International Nursing Review, 54, 219-226. Psychotherapy in Practice, 58 (11), 1433–1441. DOI: 10.1002/jclp.10090 Purvanova, R. K. & Muros, J. P. (2010). Gender differences in burnout: A meta analysis. Journal of Vocational Behavior, 77(2), 168-185. Salazar-Clemena, R. M. (2002). Family ties and peso signs: Challenges for career counseling in the Philippines. The Career Development Quarterly, 50(3), 246-256. Schaufeli, W. (2017). Applying the job demands-resources model: A “how to” guide in measuring and tackling work engagement and burnout. Organizational Dynamics, 46, 120-132. Sheppard, K. (2015). Compassion fatigue among registered nurses: Connecting theory and research. Applied Nursing Research, 28(1), 57-59. Sinclair, S., Raffin-Bouchal, S., Venturato, L., Mijovic-Kondejewski, J., & Smith-MacDonald, L. (2017). Compassion fatigue: A meta-narrative review of the healthcare literature. International Journal of Nursing Studies, 69, 9-24. Socha, A., Cooper, C. A., & McCord, D. M. (2010). Confirmatory factor analysis of the M5-50: An implementation of the International Personality Item Pool Item Set. Psychological Assessment, 22(1), 43-49. Sprang, G. Clark, J & Whitt-Woosley, A. (2007). Compassion fatigue, compassion satisfaction and burnout: Factors impacting a professional’s quality of life. Journal of Loss and Trauma: International Perspectives on Stress and Coping, 12(3), 259-280. Stamm, B. H. (2005). The Professional Quality of Life Scale: Compassion satisfaction, burnout & compassion fatigue/secondary trauma scales. Idaho State University: Sidran Press. Stamm, B. H. (2010). The Concise ProQOL Manual. Pocatello, ID. ProQOL.org. Warlick, Ingram, Vuyk & Multon (2019). Concurrent validity and expanded interpretation of the M5-50. Current Psychology, doi: 10.1007/s12144-018-0106-2. Yu, H., Jiang, A., & Shen, J. (2016). Prevalence and predictors of compassion fatigue, burnout and compassion satisfaction among oncology nurses: A cross sectional survey. International Journal of Nursing Studies, 57, 28-38. Zellars, K., Perrewe, P., & Hochwarter, W. (2000). Burnout in healthcare: The role of the five factors of personality. Journal of Applied Social Psychology, 30(8), 1570-1598.
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The application of loss modeling pricing for group health insurance in the Philippines
Soleil G. Baria and Tomas S. Tiu De La Salle University [email protected]
Abstract
The paper aimed to demonstrate the application of risk management and loss modeling on the estimation of health insurance product prices and the advantages and disadvantages of the Frequency-Severity Method over the traditional Loss-Cost approach in which only claims severity is estimated. The results of the study showed that by classifying data according to its similar characteristics, the risk of wrongly specifying a best-fit probability distribution is minimized, percentiles can be determined through Maximum Likelihood Estimation thus avoiding the use of the central limit theorem. The concluding segmented pricing equation is more effective in expressing in numbers the primary pricing drivers. Claims data were right-skewed heavy-tailed and best-fitted into the Weibull distribution by Anderson Darling and p-value estimates. Results suggests a superior pricing model for group health insurance reflecting better probable loss incidences and better reserving practices.
Key Words: health maintenance organization, health insurance, loss model, pricing model, claims modeling, standard risk premium, frequency-severity method, Weibull distribution, maximum likelihood, conditional tail expectation ______
Introduction
Health Maintenance Organizations (HMOs) were established to create products that help individuals narrow down their costs of out-of-the pocket payment for medical expenses. Unlike other kinds of insurance companies, HMOs are not allowed to include savings and investment components into their products. The sustainability of the business and the profitability of each contract is defined by competitive yet reasonable premiums. While insurers manage to create competitive rates, reasonability has always been in question, a study of Albert (2014) suggests that the culprit for imbalanced health plan prices is marketing pressure.
Often, insurers put insurance prices down to remain competitive. In the long run, this has been proved to be counterintuitive. Fuhrer (2015) explained a common pricing dilemma wherein the insurer would tend to attract groups with higher-than-manual claims experience, otherwise called ―over-utilizers, as those groups would be quoted lower premium rates by that insurer, causing an eventual deficit. Albert (2014) further reinstates that health insurers will not make money by writing low claims groups but make money by quoting appropriate rates for all groups.
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In the Philippines, the HMO industry is headed toward tighter financial regulation when Executive Order 152 was passed in 2015. The law transferred the supervision of HMOs in the Philippines from the Department of Health to the Insurance Commission. The law has made way for heightened standards in doing business, taking an industry without any regulation to a highly regulated financial institution with high barriers to entry.
Local actuaries are encouraged to move away or to supplement their reserving practice in the pricing of health insurance products with innovative pricing, not reserving, methodologies that are adaptable to change. Most of the approaches, including the Frequency – Severity approach that is used in the model proposed in this study, are already implemented in developing markets and mature markets where there is a growing demand for new health insurance products that complement trends in the general economy.
This study proposed a Pricing Model that focused on the modelling of losses based on the two dimensions of risk: frequency and severity, as it is estimated in the use of empirical data. Caughron (2012) has identified that the frequency and severity approach in the analysis of loss is the definite starting point of loss development analysis and price modelling.
Following the conclusion in the research of Boland (2006), insurance data contains relatively large claim amounts, which may be infrequent. There is a need to find and use statistical distributions with relatively heavy tails and highly skewed.
The study explored the inquiry, will loss model-based pricing, through the frequency-severity method, provide rates with lesser loss potential as compared to prices from the traditional pricing method?
The scope of the model is to estimate prices for a standard group risk profile, given a standard group plan with a benefit threshold assigned as the maximum benefit limit.
Due to high level of confidentiality of medical claims and policyholder information, the study was limited to the use of two sets of claims data each provided by two Health Maintenance Organizations under a Non-Disclosure Agreement. The claims data was limited to corporate customers, particularly principal policyholders.
With the aforementioned limitations in data samples, the underlying statistical models found in the study do not adequately reflect the whole of the HMO industry, however, are meant to illustrate the applicability as a contribution to the literature on the loss modeling.
Review of Related Literature
In common pricing practice the starting point is the determination of expected claims based on base rates, loading factors, membership and exposure information, or the estimation of the future cost to insure based on historical data as explained in a study by Pashayan (2009).
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One of the challenges in studying exposure information or experience claims are it is subject to asymmetric information. Traditional Risk Theory as applied to insurance believes that Risk Classification can address the gap created by asymmetric information (Porrini, 2015).
The consequences of asymmetric information, or the lack of the right steps to managing such, have a direct effect on prices because of the gap between the forecasted and actual cost to the insurer. A health plan‘s average and marginal costs are different functions of the identity of its enrollees, for a given set of health insurance plans, hence administrators and/or the market equilibrium will have difficulty setting premiums optimally (Akerlof, 1970; Newhouse, 1996; Cutler and Reber, 1998).
In an effort to manage risk from asymmetric information, a risk classification system is created to enhance efficiency possibilities (Crocker, 1999) by ensuring that losses with similar characteristics are grouped to receive similar treatment or cost. The classification of risk by frequency and severity is assisted by a loss threshold through the security level ρ.
The Collective Risk Theory begins the approximation of aggregate losses at level of the portfolio as a whole, contrary to the individual risk theory which starts in the investigation of individual risks (Kahn, 1962). The Collective Risk Theory is applied as the collective risk model which assumes that the aggregate loss S is a compound distribution of a frequency and severity distribution (Boratynska, 2008). The theory allows for the assumption that frequency and severity are independent variables; this provides simplification that the pure premium is simply the product of the two estimates.
The approach to the assumption of independence was developed by Jorgensen and de Souza (1994). Jorgensen and de Souza (1994) directly modeled the risk or expected cost of claims per insured unit, p. Further study from Garrido, Genest & Schulz (2016) defined the independent aggregate claims model mathematically. S represents the total amount paid out in claims over a fixed time period , where N is the number of claims incurred or the claim frequency such that Y1,..,N is a claim amount.
The Extreme Value Theory (EVT) deals with large deviations from the mean, so that it can be interpreted as random observations from population with some underlying―distribution of excesses (Levine, 2009). It provides asymptotic behavior of the extreme realizations (Alfarano & Lux, 2010) and a scientific language for translating management guidelines on these boundaries into actual numbers (Embrechts, 1999).
A key concept on the Extreme Value Theory is the limiting distribution of the excess over a threshold must be one of a small number of distributions (Klugman, 2008). It is concerned with two types of losses: the distribution of losses in excess of a threshold, high severity-high frequency losses, and the largest loss over a period of time, high severity-low frequency losses.
The strategy to the management of high severity-high frequency losses is to avoid them or exclude them in contracts when thresholds are inadequate to control the loss the Conditional Tail Expectation (CTE), also known as the Tail Value-at- Risk (TVaR). CTE is a preferred alternative of the Value-at-Risk (VaR) as a risk measure in expected loss for heavy tailed distributions that is used to estimate losses (Necir, Rassoul & Zitikis, 2010).
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High severity-low frequency losses are composed of, from the given data set, an amount of losses that exceed the security level ρ by a constant α. Examples of this type of loss in the health insurance setting are pandemics and late onset terminal illnesses. They impose a risk that cannot be avoided by exclusion policies and regulation.
Compared to seasonal, high impact losses, shock losses are challenging to predict because of the lack of data to support a trend. During the examination of historical data, shock losses are either excluded (Sharma & Ahluwalia, 2010) that leads to understated premiums, or numerically replaced by the average values obtained from a longer period of time. Shock loss data may also cause distortion during the year or year annual premiums such as drastic increases and decreases.
High impact losses are reinsured. The Philippine HMO industry, however, has yet to introduce a reinsurance strategy in their business model. It is critical for Product Pricing to be able to withstand the first onset of these kinds of claims by studying a parametric distribution to describe its occurrence.
There are two approaches to modeling claims experience, the traditional Lost Cost Approach and the loss modeling approach. The traditional approach, or the Loss Cost Approach, looks at data by the total amount per year without the consideration for individual losses. The approach was created when data was sparse and technology was expensive.
The advantage of using this approach is its simplicity, an insurer will only need to study and update only one model (Caughron, 2012). Under-regulated markets, like in the Philippines, have been using this approach taking form of the Chain Ladder Method, a reserving method (IIAP, 2016). The problem with using reserving as a substitute for pricing is the former is concerned with what is, while the latter is concerned with what will be (Werner & Modlin, 2016) and models borne from this approach can often mask important patterns in the data (Korn, 2015). This method of pricing is constrained to circumstances when there are no benefit changes, no new illnesses to cover, when there are few claims or regularly sized claim amounts (IIAP, 2016).
Further, it was emphasized by Denuit, Marechal, Pitrebois & Walin (2007) that the focus in the estimation or determination of expected claims is not to measure just the relationships and circumstances that give rise to the claim numbers but rather to estimate the amount the insurance company will have to pay given consequences of random outcomes, hence, the loss modeling approach.
In loss modeling, Fuhrer (2015) explains that while the majority of members incur a relatively low annual claim amount, there is typically a small percentage that incurs an extremely high amount, thus raising the overall group average (mean). The authors concluded with a distribution showing non-normality, of which was described by Gray & Pitts (2012) as positively skewed in a risk modeling undertaking.
The non-normality conclusion has been undisputed in modern loss modeling literature (Werner & Modlin, 2016). Hence, it should be noted that studies reviewed in this section all began with the same non-normality assumption and became the motivation to explore hypothetical distributions most fitting of insurance losses.
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In a study of the application of loss distributions to general insurance and reinsurance products, Pacakova & Brebera (2015) used a parametric estimate through statistical software to test the fit of claims severity data to hypothetical severity distributions: Gamma distributions, Lognormal distribution and the Weibull distribution, concluding that the Lognormal distribution is the best fit, additionally confirming that the Pareto distribution is the best fit for extreme tails (Pacakova & Berebera, 2015).
Even with a consistent conclusion leaning towards the lognormal distribution, the study of and Pacakova & Berebera (2016) showed underestimations at middle claim intervals and tails were still found in the lognormal distribution.
Methodology
This paper used a purposive sampling method and requested data from Health Maintenance Organizations operating in the Philippines. Two (2) local Health Maintenance Organizations (HMOs) volunteered to provide comprehensive claims data and standard prices under separate legally binding Non-Disclosure Agreements that specifically necessitates anonymity for both companies. Insurance claims data hold the highest level of confidentiality in the insurance field. It contains not only the customers’ personal and medical information, but also information that may implicate a company’s competitive advantage.
Primary data was used in the calculation of prices from the proposed model. Historical claims data were provided by both companies in raw electronic format based on consent given by their executive, legal and actuarial teams. This research shall refer to the companies as Company A and Company B.
Company A has been in operations since 2003 and reorganized in 2015 as an independently operating Health Maintenance Organization. Their portfolio boasts at least 1,610 corporate clients and 60,000 executives and employees. Although the company did not release financial statements to the public and have withheld this information to the researcher, the company passed the minimum capital and reserve requirements set by the 2015 HMO regulatory law.
Company A has provided a comprehensive 2003 to 2015 data of Principal member claims containing: billed amount, payable amount, type of claim, illness information, billing dates, policy holder contract dates and Principal policy holder birthdates. After pre-processing, the time horizon was narrowed down to In-Patient and Out-Patient claims and to a 10-year period of January 1, 2006 to Dec 31, 2016, because other types of claims: Emergency, Maternity and Annual Physical Examination were confirmed by the company as add-ons to standard group pricing. Additionally, claims from January 2003 to December 2005 compromise less than 1% of the total claim volume.
Company B has been in operations for three decades as a multi-line insurer serving over 1,000 multinational and domestic corporations and 365,000 executives, employees and their dependents. The company claims ranking first in Group Health Insurance among multi-line insurance companies from 2006 up to the present providing health insurance coverage to high risk industries. According to a publicly released independent auditors report by SGV in 2016, the company has a Loss Ratio of 64%.
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Company B has provided a raw 5-year comprehensive data of Principal member claims from January 1, 2012 to Dec 31, 2016, containing: billed amount, payable amount, type of claim, illness information and billing dates. Also, the company has provided data on the average age per company and current year number of principals per company.
Although the two companies have different time horizons, both have submitted at least 100,000 claims each for modelling (Table 1) which is a reasonable sample for modelling. The primary concern is not the time horizon of the data, but the reasonability of the volume of claims or the ideal length of time relative to how long before an HMO can accumulate a number of data points needed by the software to come up with best fitting distribution. Second reason is that insurance process needs at least three months to actualize Included but Not Reported (IBNR) claims. Both loss data provided comply with these two considerations.
Both data providers confirmed that their group medical benefits programs are renewable annually and subject to underwriting and pricing adjustments based on yearly claims experience.
Table 1 Company Data Summary Company A Company B Total Contract Years 10 5 Number of insured companies in the study 1,664 25 Total Number of members 55,936 26,272 Number of claims included in the study 434,115 170,090
The research methodology is broken down in two phases: Risk Classification and Loss Estimation. The average age and average group size of the portfolio were identified first. By industry standard, these two factors are closely linked to the characteristics of the loss portfolio and define the limitations of the Standard Risk Premium.
It should be noted that the average group size and average age takes into consideration the most stable number of principals in a contract year. Since group health insurance deals with corporate groups, principal changes in insured is directly affected by employee attrition and hiring. The potential for loss is found when a low risk individual is replaced by a high-risk individual. Another risk is realized when there is a significant drop or increase in the number of principals in the middle of the contract year, such that average age will change and is no longer aligned with premiums.
For Company A, the average age and optimal group sizes were computed. For Company B, the study used the data provided by the company.
Billed amount data was organized by the total claim per event (per member per incident per occurrence date). The Accident Year Loss Aggregation (Year of Loss Occurrence Date) approach was used to group annual data. This is critical in the application of correct inflationary multipliers based on the Philippine Consumer Price Health Index.
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The adjusted billing amounts were analyzed for reasonability through the empirical analysis of year-on-year changes at three levels: Per Member, Per Company and Overall Portfolio. Any inconsistencies and significant changes were investigated.
In-Patient Data and Out-Patient Data are separated for two reasons: volume and behaviour. This follows observations from several researches on medical claims costs wherein inpatient claims and outpatient claims are modelled separately because of its distinct differences in program features which also drive differences between severity and frequency (Frees (2010), Yamamoto (2013), Zlibar (2016), Bednar (2017).
The Severity and Frequency thresholds were established through parameter estimation in MINITAB 18. By default, MINITAB 18 uses Maximum Likelihood Estimation.
The 95th percentile is assigned as the Severity Threshold between Attritional Losses and Shock Losses. It is also the Maximum Benefit Limit of the product plan being priced
The Frequency scores were identified for a range of values for the average yearly frequency given by the formula (Klugman, 2008).
Once thresholds per risk score have been identified (Figure 1), the values are also verified through the assistance of a histogram. Severity scores are based on parameter estimation from MINITAB 18, each score representing loss amounts within a percentile. Frequency scores are based on a counting distribution, for example, the frequency score of five (5) indicates that the occurrence of loss is less than one percent (1%) of the total number of occurrences.
During the procedure of computing for the p-values and the Anderson-Darling estimates, normality was first tested against the data.
A non-normality test was performed graphically for both Company A and Company B data. From these observations of non-normality, it is evident that it was not appropriate for data to be measured by the central limit theorem. It would provide an erroneous average that would lead to erroneous standard prices.
When claims are broken down by claim type into inpatient and outpatient, parametric fitting on categorized data showed none of the data sets have a p-value greater than 0.005 for normal distribution and the Anderson-Darling statistic for the normal distribution was poorly ranked.
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Severity Likelihood % of the ABL At least 20% to 10% to 1% to Less than 70% <70% 20% <10% 1% (1) (2) (3) (4) (5) 95th to 99th (5) 5 10 15 20 25 90th to less than 95th (4) 4 8 12 16 20 80th to less than 90th (3) 3 6 9 12 15 80th to 95th (2) 2 4 6 8 10 Below 80th (1) 1 2 3 4 5 Figure 1. Risk Map
Legend Catastrophic Unacceptable Undesirable Acceptable Desirable
It was observed that outpatient claims were more frequent than inpatient claims, but inpatient claims were significantly higher than outpatient claims. Concluding non-normality and finding differences in claims and behavior in claim types, the exposures were then fitted to non-normal continuous distributions using MINITAB.
Models for Attritional Losses
The Base Risk Premium is simply the product of the result of the Severity Model and the Frequency Model.
The severity is particularly concerned with the average of the worst 5% losses at the tail of the distribution, while the frequency is concerned with the average of all the claims under this risk class. Following methodologies highlighted in the study of Sharma & Ahluwalia (2010), the base risk premium pricing equation is adjusted by introducing a constant k in both parts of the equation, E(S) = E(N) × kN × E(Y) × kY.
The constants kN and kY are external inflation factors for severity and frequency and if there is a change in external factors, a value can be assigned. Shock Losses are high impact, low frequency losses and is the difference between the theoretical model and the actual event. Shock Losses are identified through the risk map as suggested by the analysis of frequency and severity data.
The primary reason for excluding these losses and not applying the Tail Value-At- Risk to estimate losses is that, that Value-at-Risk (or the Tail Value-At-Risk) can only quantify the probability that a loss exceeds a certain level, but the magnitude of such a loss is not specified
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(Harlow, 1991). Adapting the mathematical description of Levine (2009), the Extreme Value Theory as the cumulative distribution function of the excesses denoted by Fu (y) as defined for non-negative.
The output of the two statistical models for Attritional Losses and Shock Losses of a particular claim type—in-patient claims or out-patient claims, is a Standard Risk Premium, Standard Risk Premium Per Claim Type = E(S) × λ.
The standard risk premium is the amount charged to a group with an average age same as the portfolio average age, with the size of the most sample group within Private Room benefit in the portfolio, with a Maximum Benefit Limit equal to the threshold u identified during risk classification.
The Combined Loss Model
The combined model is the final pricing model where estimations for attritional losses of both inpatient and outpatient claim, and shock losses of both inpatient and outpatient claims are joined to produce the final standard risk premium.
The Standard Risk Premium produced on combined loss model is interpreted as the amount to be paid the following year for a group of n-number of principals with an average age-a, for a Private plan with a benefit limit of u.
Standard Risk Premium = (E(S)IP × λ IP) + (E(S)OP × λ OP)
Attritional Losses, E(S), were estimated through the separate analysis of a Frequency Model and a Severity Model, under the independence assumption. Probability Distributions were fitted on the loss data, indicating the best fit distribution as the distribution with the highest p-value and the smallest AD statistics. The chosen distribution also conforms with fundamental data characteristics of insurance claims.
The estimate for the occurrence of Shock Losses or the high impact low likelihood event, represented by λ, were guided by the Extreme Value Theory.
Evaluation of the Risk Premium
The calculated standard risk premiums were compared to the equivalent of the empirical premiums (published rates) provided by the two companies: for Company A, the amount is Php 9,300.77 for the year 2017, for Company B the amount is Php 20,462.40 for the year 2018. This is done on an aggregate level by choosing sample groups within the companies ‘portfolio that fit the same group size and the average age. The premium is multiplied to the number of principals enrolled to obtain to aggregate premium of the portfolio. The losses of the samples were further trended to the year the price is applicable, that is 2016 for Company A, and 2017 for Company B.
Two supplementary analyses were performed. The first analysis is a comparison of the year- on-year modelled premiums, 2013 to 2015, of the two companies involved in this study. The second analysis is a comparison of the modelled risk premiums of each company and a modelled risk premium of their combined claims data.
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Such analysis was undertaken to provide more insight on the differences of each HMO’s loss patterns and their relative differences from the industry premium theoretically represented by their combined claims.
Results and Discussions
After concluding the non-normality and finding differences amongst claims trend behavior between two claim types, the exposures were fitted into possible continuous distributions.
The mean of the distribution is approximately four times less than the 95th percentile, hence, if used in pricing, there is a probability that the premium charged is four times smaller than the average claim. In aggregate, the funds may not be able to sustain continuous high impact losses, or losses from companies in high risk industries.
The 95th percentile is the Maximum Benefit Limit of the product priced in this study, the value is also incorporated as the boundary between high risk claims and low risk claims during assignment of impact scores for risk mapping.
Severity scores and likelihood scores were incorporated into a risk map for Company A and Company B in order to determine attritional losses (risk score below 16) and shock losses (risk score 16 and above).
For the modelling of frequency data, the results from MINITAB measured against the Poisson distribution, hence, risk scores were assigned based on manual ranges resulting to the frequency mapping in Table 2 for Company A and in Table 3 for Company B.
Table 2 Company A range of frequency values per likelihood score Company A In-patient Out-patient Likelihood Score Range Number of Occurrences Range Number of Occurrences 1 >=450 3638 >=10000 140550 2 300 to < 450 3236 5000 to < 10000 962270 3 100 to <300 2639 1000 to < 5000 93094 4 20 to < 100 2718 20 to < 100 1140 5 < 20 153 <20 153
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Table 3 Company B range of frequency values per likelihood score Company B In-patient Out-patient Likelihood Score Range Number of Occurrences Range Number of Occurrences 1 >=1000 5217 >=10000 22770 2 500 to < 1000 6135 5000 to < 10000 14708 3 100 to <500 500 1000 to < 5000 2843 4 20 to < 100 32 100 to < 1000 1442 5 < 20 71 <100 189
Attritional losses and shock losses for each claim type were also processed to find the best fitting distribution. Results from the segmented data are in agreement with earlier results after concluding the Weibull distribution as shown in Table 4 where in the distributions Weibull, Smallest Extreme Value (SEV) and Largest Extreme Value (LEV) were the only the only distributions that consistently resulted to p-values of < 0.010. SEV and LEV are derivations
Table 4 Estimates for the Anderson Darling Statistic for Company A (MINITAB) Distribution In-Patient Out-Patient Attritional Attritional Attritional Distribution Attritional (Company (Company Shock (Company Shock (Company A) A) B) B) Weibull 167.793 3480.237 308.111 * 130021.603 48076.198 SEV 25.631 544.763 44.431 11333.398 * * LEV 18.142 40.918 13.419 82.923 275.174 29.643
From 2010 onwards, the industry moved towards documenting and indexing high risk industries, formally excluding them from standard insurance portfolios and products.
Since pricing is more concerned with the current and future state of the business, the outlier- years have been excluded in the analysis of Attritional losses, being that attritional losses are the reflection of standard insured behaviour. The model does not discount the fact that a company is always exposed to asymmetric information, which may be a cause for unknowingly insuring a high- risk group under a standard- priced program, hence information from 2008-2009 were still included in the analysis for Shock Losses.
Following the equation for the base risk premium, the external inflation factors kN and kY were provided and assumed as 1.00 by default in Table 5, that is, there is no inflation expected in the next period. This value may change under the discretion of the company.
The total cost represents the cost to cover each type of claim, the sum of the two values is the standard risk premium for a group of n-number of principals with an average age a. The Maximum Benefit Limit of the product is the 95th percentile of in-patient claims.
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Table 5 Components of the Underwriting Cost Company A Company B Cost Component In-patient Out-patient In-patient Out-patient E (N) 115,028.04 4,565.68 146,904 6,144.60 E (Y) 0.0965 0.5546 0.071 0.7773 λ N 526,828.42 9,620.64 245,329.68 28,203.71 λ Y 0.0097 0.2133 0.0369 0.5618 kN 1.00 1.00 1.00 1.00 kY 1.00 1.00 1.00 1.00
Table 6 Benefit Summary Per Company Plan and Benefits Company A Company B Portfolio Average Age 36 to 41 35 to 40 Portfolio Optimal Group Size 70 to 100 60 to 90 Maximum Benefit Limit 110,000 100,000 Room and Board Private Private
Modeled claim amounts are based off the total billed amount or the full amount of the claim as opposed to the total covered amount or the amount shouldered by the insurer.
If modelled prices exclude Shock Loss scenarios in the analysis, the modeled premium for Company A was only 11.10% higher for Company A, and for Company B a 25.69% drop was observed. This means that Company A empirical premiums only have a small margin for unwarranted high-risk claims, while Company B will suffer a loss.
The same steps were performed on the combined claims of Company A and Company B with the resulting premiums assigned as the theoretical pricing benchmark. Consistent with the findings for the best-fit distribution, the Weibull distribution has the highest ranked Anderson Darling Statistic amongst distribution p-values at least 0.0010.
Conclusions and Recommendations
The findings of the research demonstrated that through risk classification, information can be dissected or broken down into measurable data that is helpful for a problem to be effectively addressed.
The proposed pricing model, following the frequency-severity method, allowed for more accurate loss distribution results and produced a segmented equation where in each type of claim with a different behavior had a defined impact to the price, which made it easier to control the cost to insure.
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In the case of insurance claims used in this study, both sets of claims were described to be right-skewed and heavy-tailed, accepting the assumption of non-normality. Further conclusions on claims behavior were only discovered after data was broken into benefit types: inpatient and outpatient data. In both datasets, it was evident that the primary influencer for in-patient claims size is the claim severity or occasional losses with large amounts, while out-patient claims were primarily driven by frequency or small losses that occur often. This information on the characteristics of claims was significant in controlling the benefit plans and limits and the price of an insurance product.
The use of this claim behavior information was demonstrated through the analysis of the loss distribution that best fitted the data. This step was relevant in determining the parameters in each risk score and the benefit limit. Combined data of inpatient and outpatient claims have unconvincing Anderson Darling measures and p-values. The separate analysis for inpatient and outpatient data showed reasonable measures of best fit for the Weibull Distribution. This conclusion is consistent across Company A’s in-patient and out-patient data and Company B ‘s in-patient and out-patient data.
Evident with the frequency-driven characteristics of out-patient claims, it was not enough that expected losses be modelled by severity alone, the frequency of claims was modelled against the Poisson distribution. Chi-square values were inconclusive for the Poisson distribution, but despite this, claim counts were still effectively categorized by a counting distribution which values were computed through the equation for the frequency of a claim. By determining the loss distributions, parameters were defined to create risk maps with measurable thresholds between the two general risk classes: attritional losses and shock losses.
By measuring these two types of losses separately and assigning a component within the equation of the pricing model to each type of loss, the influence of shock losses or high-impact- low frequency losses on pricing became apparent and defined. It was evident that one of the two companies, through its Shock Loss Multiplier, was controlling their losses by managing the severity of their losses. The other company was controlling their losses by managing the frequency of the claims.
Glossary
Term Definition Claims data Contains the details of every hospitalization, treatment, in-patient and out- patient procedure charged by the insured to the insurer. The claims data is considered as loss data information as it is a list of liabilities of the insurer to the medical institution or practitioner (US Centers for Medicare & Medicaid Services, 2017). Shock claims Losses which occurs infrequently but of considerable magnitude (Casualty Actuarial Society, 2017) Attritional All other losses that are not classified as Shock Claims claims (Casualty Actuarial Society, 2017) Maximum A method of estimating the parameter values of a parametric model particularly likelihood for data with heavy tails or extreme observations (Klugmann, 2002) estimation
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Premium A fixed amount charged by an insurer for a specific set of benefits (Health Maintenance Organizations Act of 2013). In this study, what is calculated are pure risk premiums which refers to that portion of that rate needed to pay losses and loss-adjustment expenses. It is mathematically equivalent to the future claims cost increased by a forecasting factor (Werner and Modlin, 2016). Benefit limit A cap or the maximum amount that the insurer will cover. There are two kinds: the maximum benefit limit and the aggregate benefit limit. The maximum benefit limit is the maximum amount per illness or procedure (US Centers for Medicare & Medicaid Services, 2017). Frequency The likelihood of an event, exposure or loss Severity The impact of an event, exposure or loss Frequency- An actuarial method for determining the expected number of claims that an severity insurer will receive during a given time period, and how much the average claim method will cost. It uses historical data to estimate the average number of claims and the average cost of each claim (Caughron, 2012). Loss cost An actuarial method for determining the expected level or amount claims by a model one-dimensional severity analysis of historical data. (Caughron, 2012)
References
Akerlof, G.A. (1970). The Market for "Lemons": Quality Uncertainty and the Market Mechanism. The Quarterly Journal of Economics, 84 (3), pp. 488-500 Albert, J. (2014). Developing Group Health Credibility. Society of Actuaries: Health Watch Issue 74, 12-14. Alfarano, S. and Lux, T., (2010) Extreme Value Theory as a Theoretical Background for Power Law Behavior. Germany: Kiel Institute for the World Economy. Bednar, W. (2017). Building Actuarial Cost Models from Health Care Clams Data for Strategic Decision Making. Society of Actuaries Health Watch (83), 9-12. Boland, P. J. (2006). Statistical Methods in General Insurance. ICOTS-7. Dublin, Ireland: National University of Ireland. Boratynska, A. (2008). Posterior regret Gamma-minimax estimation of Insurance premium in Collective Risk Model. Astin Bulletin 38(1), page 277-291. Caughron (2012). Loss Cost Modeling vs. Frequency and Severity Modeling. Casualty Actuarial Society Ratemaking and Product Management Seminar. Retrieved from https://cas.confex.com/cas/rpms12/webprogram/Session4738.html Crocker, K. and Snow, A. (1999). The Theory of Risk Classification. University of Michigan Business School. Retrieved November 30, 2017, from http://www.personal.psu.edu Cutler, D. M. and Reber, S. J. (1998). Paying for Health Insurance: The Trade-Off Between Competition and Adverse Selection. The Quarterly Journal of Economics, 108 (2), 33 -466. Denuit, M., Marechal, X., Pitrebois, S. and Walhin, J. F. (2007). Credibility Models for Claim Counts. Retrieved from https://doi.org/10.1002/9780470517420.ch3. Embrechts, P., Resnick, S. and Samorodnitsky, G. (1999). Extreme Value Theory as a Risk Management Tool. North American Actuarial Journal, 3 (2), 30 - 41. Frees, E. (2010). Regression Modelling with Actuarial and Financial Applications. Cambridge University Press.
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Fuhrer, C. (2015). A Practical Approach to Assigning Credibility for Group Medical Insurance Pricing. Society of Actuaries, 1-14. Garrido, J., Genest, C. and Shulz, J. (2016). Generalized linear models for dependent frequency and severity of insurance claims. Insurance: Mathematics and Economics. 70, 205-215. Gray, R.J. and Pitts, S. M. (2012) Risk Modeling in General Insurance. Cambridge University Press, 2. Harlow, W.V. (1991). Asser Allocation in a Downside-Risk Framework. Financial Analyst Journal 47(5). 28-40. Jorgensen, B. and De Souza, M.C.P. (1994) Fitting Tweedie's compound Poisson model to insurance claims data. Scandinavian Actuarial Journal, 69-93. Kahn, P.M. (1962). An Introduction to Collective Risk Theory and Its Application to Stop- Loss Reinsurance. Transaction of Society of Actuaries, 14 (40). Klugman, S., Panjer, H., Wilmot G. (2008). Loss Models: From Data to Decisions. 3rd edition, John Wiley & Sons, 2008. 726pp. Korn, U. (2015). A Frequency-Severity Stochastic Approach to Loss Development. Retrieved November 28, 2017, from https://www.casact.org/pubs/forum/15spforum/Korn.pdf. Levine, D (2009). Modeling Tail Behavior with Extreme Value Theory. Society of Actuaries: Risk Management 17. Necir, A., Rassoul, A., Zitikis, R. (2010). Estimating the Conditional Tail Expectation in the Case of Heavy-Tailed Losses. Journal of Probability and Statistics Volume 2010, 17 pages. Newhouse, 1996 Pacakova, V. & Brebera, D. (2015). Loss Distributions and Simulations in General Insurance and Reinsurance. International Journal of Mathematics and Computers in Simulation Vol 9, 159-167. Pashayan, H. (2009). A Modern Approach to Group Pricing & Credibility. Biennial Convention. Sydney, New South Wales: Institute of Actuaries of Australia. Porrini, D. (2015). Risk Classification Efficiency and the Insurance Market Regulation. Italy: Dipartimento di Scienze dell‘Economia, Universita del Salento, Ecotekne. Sharma, P., & Ahluwalia, J. (2010). Re-Pricing Health Insurance Product. Insurance Regulatory and Development Authority, 10 (7), 18-26. Insurance Institute of Asia and the Pacific (2016). HMO Pricing. Actuarial Society of the Philippines Pricing Seminar. Unpublished. Werner, G., & Modlin, C. (2016, May). Basic Ratemaking Fifth Edition. Retrieved February 2017, from Casualty Actuarial Society: https://www.casact.org Yamamoto, D (2013, June). Health Care Costs from Birth to Death. Health Care Cost Institute‘s Independent Report Series. Zlibar, T. R. (2016). The Actuarial Uses of Health Service Indicators and Projections of Health Service Expenditures in Croatia. Croatia: F&R Insurance Consulting.
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ASEAN ICT developments: Current state, challenges, and what they mean for SMEs
Raymund B. Habaradas and Ian Benedict R. Mia De La Salle University [email protected]
Abstract
In the Association of Southeast Asian Nations (ASEAN), the different member states have been developing ICT policies and programs to raise the quality of public service delivery, and to help businesses, including small- and medium- scale enterprises (SMEs) to adapt to the changing business landscape. An examination of the efforts undertaken by the ASEAN Member States reveal a digital divide among these states, with Singapore, Brunei, and Malaysia leading the way in achieving nationwide digitalization, followed by Indonesia, Thailand, Vietnam, and the Philippines, who are attempting to bridge infrastructure gaps towards a knowledge economy, and, finally, by Cambodia, Myanmar, and Lao PDR, who are at the nascent stages of developing their ICT policies and regulatory frameworks. To address this digital divide, we suggest the open exchange of knowledge and experiences among member states to facilitate benchmarking and to encourage the adoption of innovative practices in their respective ICT sectors.
Key Words: Association of Southeast Asian Nations, information and communications technology, small and medium enterprises ______
Introduction
Information and communications technology (ICT) is revolutionizing the way people do business. According to the 2016 Global Information Technology Report by the World Economic Forum, the rise of ICT has brought about the Fourth Industrial Revolution (Baller, Dutta, and Lanvin, 2016), or more popularly known as the digital revolution. This is characterized by global and digital communications, high-density data storage and low-cost processing, and an increasing number in global users of digital technologies.
In the Association of Southeast Asian Nations (ASEAN), the different member states have been developing ICT policies and programs to help businesses, including small and medium enterprises (SMEs), to adapt to the changing business landscape. In the ASEAN ICT Masterplan 2020, various thrusts, initiatives, and action points were set along the following areas, among others: economic development and transformation, innovation, ICT infrastructure development, human capital development, people integration and empowerment through ICT, new media and content, and information security and assurance.
Essentially, the main goal of the ICT masterplan is to create a “digitally-enabled, innovative, inclusive, and integrated ASEAN community” to take advantage of the region’s shift
37 | P a g e www.paomassociation.wordpress.com towards a digital economy. Over the past years, ICT has played a significant role in terms of connectivity and integration between the different member states and their regional and global value chains. However, the development of ICT is in different stages of growth across ASEAN member states. While some member states are still emerging in their adoption of ICT, others have already established a strong foundation, and have established their ICT infrastructure and systems.
In the e-ASEAN Framework Agreement of 2000 (ASEAN, 2012), ASEAN members states are enjoined to integrate ICT development into their national policy. In the long run, this was meant to improve the competitiveness of ASEAN in the global landscape (Dai, 2008). However, the digital divide among ASEAN states calls for more action, which can be guided by the appropriate policy and regulatory environment. But what is the relevance of ICT policies and programs to SMEs in ASEAN member economies?
The ASEAN ICT Masterplan 2020 serves as an overview of the general policies being implemented to enable ICT development in the region. It is expected to be implemented throughout 2016 to 2020, with strategic thrusts tailored for the region’s transition to a digital economy. Among one of the specific components of these strategic thrusts include the promotion of digital trade through “policy innovations, awareness raising, and enabling electronic and other better modes of transactions and payments especially for SMEs”. Specifically, the rise of financial technology platforms like e-commerce opens up opportunities for many small businesses that can now take advantage of disruptive technology to compete with larger players. Needless to say, digital trade is still a young and booming industry in the ASEAN.
However, many SMEs shy away from adopting technological innovations because they perceive the costs and risks involved as being too high. Governments can address this by speeding up investments in infrastructure that will help bring down the cost ICT. This is being done by several ASEAN member states, which have deployed a wide range of programs to further develop their ICT sectors. Among some of the common practices include the implementation of an e- Government platform, national broadband, human resources training, and the development of ICT infrastructure.
Governments can also support programs that will facilitate the linkage of small businesses with sources of technological knowledge and capability. For instance, technology transfer and knowledge-sharing activities among universities, public research institutes, industrial associations, governmental, and private sector intermediaries can help companies in various stages of their business life cycle to develop innovation capabilities. As the ASEAM SME Policy Index 2014 states, the available linkages between universities and industries among ASEAN states can help improve the innovation capabilities of SMEs in ICT.
In the following sections, we look into the varied ICT policies of ASEAN member states, as well as the programs being implemented by the government and private sectors in light of the policy efforts. These sections will also discuss the variations in terms of the level of ICT development between different countries in the ASEAN.
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Sustaining nationwide digitalization: Singapore, Brunei, and Malaysia
Singapore. In the 2015 and 2016 Global Information Technology Report of the World Economic Forum, Singapore was ranked as the world’s most digitally connected country. In a nutshell, Singapore has a productive ICT ecosystem since it is home to many global technology firms such as Google, Facebook, and Alibaba. These firms aggregate many opportunities for other ICT firms as well as partner with one another and end-user companies to continue creating commercially viable solutions related to ICT. Moreover, several foreign institutions have partnered with Singapore industries like financial services and manufacturing to expand their market to Southeast Asia. Singapore also has the TechSkills Accelerator program to train ICT professionals (Economic Development Board Singapore, 2018).
Being the top-rated country in ASEAN in terms of ICT development, Singapore has had “a plethora of policies for SMEs, and that these have been a key aspect of government industrial policy” (Lim, 2016). One of these policy strategies is Infocomm 21, a market-driven, private sector oriented, and global strategy that aims to liberalize the telecommunications market in Singapore and foster technopreneurship. Of these initiatives, one of the crucial aspects that will impact Singapore-based SMEs is that of “dotcomming the private sector” by attracting top talents, spurring consumer demand, fostering an e-lifestyle, and bridging the digital divide.
Worth noting is Singapore’s “Smart Nation,” which envisions “a whole-of-nation movement to harness digital technologies to build a future Singapore, to improve living and build a closer community, empower citizens to achieve their aspirations through good jobs and opportunities, and encourage businesses to innovate and grow.” Among the strategic national projects included under this vision include the National Digital Identity, e-Payments, Smart Nation Sensor Platform, Smart Urban Mobility, and Moments of Life. The country also enables a culture of innovation and experimentation through open data, research and innovation, industry and startup ecosystem, cybersecurity and data privacy, and computational capabilities and digital inclusion (Smart Nation and Digital Government Office, 2018).
There is also a strong drive in Singapore to encourage local e-businesses to internationalize. For example, the Infocomm Media Development Authority of Singapore (IMDA) enables overseas linkages “through partnerships with industry players to set up business centers in strategic countries.” IMDA further describes Infocomm standards in Singapore as follows:
“Infocomm standards in Singapore are developed on a consensus basis and are the results of the collaborative efforts amongst the government agencies, tertiary institutions, professional bodies and the infocomm industry. The IMDA Standards Team plays a key role in fostering and facilitating the industry's participation in local and international ICT standards forums.”
In 2016, Singapore established the Government Technology Agency, which “leads technological transformation in the public sector, develops citizen-centric Smart Nation applications, nurtures ICT talent and capabilities, and builds a more intuitive and anticipatory government through digital services.” Within this agency, six capability centers are included such
39 | P a g e www.paomassociation.wordpress.com as application development, cybersecurity, data science, government ICT infrastructure, geospatial technology, and sensors and Internet of Things.
Brunei Darussalam. The ICT policy of Brunei Darussalam is centered on the National Digital Strategy 2016 to 2020, which contains three strategic outcomes: a vibrant economy powered by ICT, ICT-smart citizens, and a connected and efficient nation (Authority for Info- Communications Technology Industry of Brunei Darussalam, 2016). One of the most notable policies is the National Broadband Policy established in May 2014. The policy aims to increase mobile broadband household penetration to 85% and provide download speeds of at least two megabits per second to 95% of the population by 2017. Another is the local business development policy framework, which enables capable local ICT companies and SMEs to participate in the ICT projects of the government.
According to the National Digital Strategy, a National ICT Policy is in the works for Brunei and is said to take “considerable time and effort.” To enable this, the following key roles are being undertaken by their government: study, develop, and issue new essential ICT policies, clear and approve changes from periodic review of existing policies, administer compliance through annual checks, and issue ICT-related general orders.
There is a need for the country towards a mindset change to “transition to a new knowledge- based economy and embrace ICT extensively.” The strategy recognizes that, “the people, businesses and the Government of Brunei Darussalam must be prepared to do things differently and adapt to new ways of learning, living, doing business, staying ‘connected’ and delivering public services.” One of the critical sectors being the SMEs, adapting to the new knowledge-based economy by embracing ICT will, in the long term, reap several benefits for these companies.
In support of the above-mentioned policies, Brunei Darussalam introduced the e- Government initiative, which is managed by the e-Government National Center (SEACOOP, 2010). Under this, the Digital Government Strategy for 2015 – 2020 aims to achieve a “digital government” by 2035, and “to lead the digital transformation, and make government services simpler, faster, and more accessible.” The program focuses on six key areas: advancing digital services, implementing universal access for government systems, optimizing digital assets, strengthening security, enhancing stakeholder engagement, and developing enterprise information management capability (e-Government National Center, 2017).
The e-Government initiative has shared services across key functions in government. One of these include the One Government Network, whose aim is “to establish and connect agencies in accessing integrated e-services as well as internet from a central gateway.” This platform is useful for streamlining and optimizing the services being offered by the government in a single, centralized source. This could translate to substantial reduction in transaction costs for SMEs that have dealings with multiple government agencies.
Another initiative is the One Government e-Communication, which aims to improve the ways by which different government agencies work together and encourages the development of ICT capabilities in different functions of the government. As a communication platform, it offers email, office communicators, and an active directory which the different government agencies can
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Malaysia. In 2016, Malaysia released its Public Sector ICT Strategic Plan 2016 to 2020, which details its policies and programs in line with ICT implementation in the country (Malaysian Administrative Modernisation and Management Planning Unit, 2016). Within the strategic plan is the ICT Framework 2016 to 2020 which consists of four main components: ICT vision, ICT strategic thrusts, enabling ecosystem, and basic principles. These components address several points of ICT development in Malaysia.
For the past years, Malaysia has undergone a rapid transformation of its ICT sector (Maynard, 2010), particularly in its telecommunications networks, national policies, institutions, and regulatory regimes. During the 2015 Forum Digital Service Repository, the Malaysia Administrative Modernization and Planning Unit stated how applications such as computing, big data analytics, open data, and enterprise architecture had been crucial in providing opportunities for the ICT framework of Malaysia. Technologies such as the Internet of Things (IoT), for instance, were highlighted. According to the Chief Secretary of the Malaysian government (Kelleher, 2015): “With the combination of public sector policies and the strategic utilization of information by the public sector, people on the forum showcase can provide an up-to-date innovation on how our everyday lives will feel more connected to IoT”.
Malaysia also has a National Big Data Analytics (BDA) Roadmap (MDEC, 2016), making it one of the few countries that have a structured BDA to “fully unleash the value of big data.” The BDA Roadmap’s main strategic initiatives include the proliferation of BDA usage in the private and public sectors, and building the BDA industry in Malaysia. As what can be seen in the current ICT framework of Malaysia, the country is on the way to further develop its ICT sector and take advantage of current technologies.
In line with the vision of digitalization and ICT development in various sectors of Malaysia, its public sector has several programs in place. These include digital services, data-driven government, cybersecurity, ICT governance, and a professional and capable workforce (Malaysian Administrative Modernization and Management Planning Unit, 2016). Digital services, for instance, aim to integrate various government services through a single platform that can be accessed by the Malaysian people. These services range from daily transactions to essential government services, including those availed of by small businesses.
In Malaysia’s education sector, the use of ICT has proven to boost the effectiveness of schools (Carroue, 2013). With the use of social media, education software, laptops, and fast internet connectivity, school children are immersed in a digital educational environment. The value of adopting ICT in the education sector and any other sector is that it enables faster and direct communication, lessens the digital divide across different people, and optimizes several processes. Recently, the Malaysian government announced that it is focusing on several key ICTs: Internet of Things, cloud computing, cyberspace security, and big data analytics (United States Department of Commerce, 2017). The common denominator among these technologies is the processing of an immense amount of data. These data are directed to the Big Data Analytics platforms of Malaysia,
41 | P a g e www.paomassociation.wordpress.com are assessed, and provide valuable knowledge that will help map out the development of the country in several sectors, including the military, the manufacturing sector, the education industry, the financial sector, and urban planning. The use of these data is paving the way for a more optimized, efficient, and sustainable Malaysia.
Singapore, Brunei, and Malaysia may as well be at the forefront of ICT development in the region. Being the most digitally-connected states in the ASEAN with their utilization of nationwide platforms for digitalization, promotion of a startup and innovation ecosystem, encouragement of local e-businesses to internationalize, and nationwide implementation of big data analytics platforms, these three countries are in the process of sustaining these initiatives and even moving further.
In between infrastructure gaps and the road to a knowledge economy: Thailand, Philippines, Vietnam, and Indonesia
Thailand. In alignment with the Thailand 12th Social and Economic Development Plan for 2017 to 2021 and the ASEAN ICT Master Plan, the Thailand 4.0 Strategy was recently formulated. This strategy focuses on the progression of ICT development and investments, country infrastructures, quality of higher education system, business sophistication, and innovation. Thailand’s Ministry of ICT has also launched various ICT policies and programs for ICT administrators of different economic sectors because ICT is seen as an engine of development for the country (Wongwuttiwat and Lawana, 2018).
The Thailand 4.0 Strategy is also referred to as Digital Thailand, which aims to transform the existing economy into a “value-based and innovation-driven economy” with the use of digital technologies. Its purpose is three-fold: “(1) building knowledge, technology, innovation, and creativity in order to release the middle income trap; (2) building social security in order to drive the country forward without leaving anyone behind and to enhance an equality society; and (3) building sustainability to balance economic development” (Thailand Board of Investment, 2017). A complementary national ICT policy to Thailand 4.0 is the ICT Policy Framework (2011 – 2020), which aims to develop the Thai ICT industry as a leader among ASEAN economies. Thailand’s ICT Ministry also intends to certify standard qualifications for ICT professionals, allowing them to be accredited across ASEAN nations. Another notable national ICT policy is Thailand’s Master Plan on ASEAN Connectivity, which aims to boost Thailand’s ICT competitiveness.
The Ministry of Digital Economy and Society, formerly known as the Ministry of Information and Communication Technology, is at the helm of developing Thailand’s ICT sector. In several sectors of Thailand such as government, industry, commerce, education, and society, the Thai government aims to integrate the digital and knowledge-based economy with the use of ICT (Thailand Information and Communication Technology Policy Framework, 2011).
ICT is widely used in the education sector of Thailand, not just in terms of the courses and programs being offered, but as well as the integration of ICT in the daily lives of students. It began under Thailand’s National IT Policy 2001 – 2010, where one of the main goals is e-Education (Makaramani, 2013). ICT in Thai education focused on programs in “lifelong learning, computer literacy, human resource development, virtual education, and creation of useful information,
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The application of ICT in Thailand’s education sector has brought forth several successes including “setting the internet backbone in the country, schoolnet project, princess IT project, awareness of new learning approach, and acquiring of hardware, software, digital contents, and networks for every school.” Challenges include human resource and professional development for in-service teachers, administrators, and personnel at all levels. Quality networks and infrastructure among Thai schools in rural areas are challenges as well.
Philippines. The Philippines has created a number of policies and plans on ICT such as the National Broadband Plan, National Cybersecurity Plan 2022, Philippine Framework for the Digital Terrestrial Television Broadcasting Migration Plan, and eGovernment Master Plan 2.0. A number of published policies can also be accessed in the website of the Department of Information and Communications Technology (DICT, 2018).
During a 2014 forum held by the Philippine National Academy of Science and Technology (NAST), the long-term strategic development plan of the national ICT infrastructure was discussed. According to the NAST President, there is a need to fix the ICT infrastructure in the country particularly in terms of corruption, bureaucracy, and the existing infrastructure itself. With the massive flow of information through the Internet and across geographical boundaries, the ICT infrastructure of the Philippines must keep up. Furthermore, although there are available digital technology solutions already, the ICT infrastructure of the country is not sufficient to take advantage of them.
The Department of Information and Communications Technology (DICT), which was established in 2016, is expected to be the trailblazer of ICT development in the Philippines. With the government climbing in the United Nation’s ranking for e-government development (DICT, 2017), and over 25% of Philippine businesses forecasted to digitally improve their products and services by 2020 (International Data Corporation, 2017), ICT is an engine for growth in the country. Among several programs of DICT include the ICT ecosystem development, national connectivity, e-Filipino, e-Government harmonization, e-Civil Servants, Next Wave Cities, ICT- enabled startup, and Stepping-up the Value Chain (Department of Information and Communications Technology, 2018).
There is also a wide range of other projects being developed by other agencies such as the Department of Science and Technology (DOST). Several projects are focused on improving and making government services more accessible to citizens. Some noteworthy projects include the Philippine Health Insurance Corporation’s Personally-Controlled Health Centers, which are owned by patients and co-managed by their health providers such as hospitals and clinics (Balucanag-Bitonio, 2013). Another is the e-LGU (local government unit), which aims to make several services of the LGUs electronic and online, thereby providing more convenience to individual citizens and businesses. In 2015, the DICT and DOST launched the “Free Wi-Fi Internet Access in Public Spaces” with funds of $66 million.
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One of the main challenges for ICT development in the country include continuing to upgrade its telecommunications infrastructure to keep up with the increasing demand for broadband. As of 2015, the average internet speed in the Philippines is 3.2 megabytes per second— the second slowest in Asia Pacific. There is also a lack of competition in the telecommunications carrier industry, with the Philippine Long Distance Company and Globe Telecom accounting for 70-percent and 30-percent market share, respectively (United States Department of Commerce, 2017).
Vietnam. A report by the International Data Corporation (2016) shows that the overall ICT policy framework in Vietnam is comprehensive “and complex” with several policies geared towards ICT development. Among some of these policies include the socioeconomic development framework, the cybersecurity governance framework, the e-Government policy, and the Vietnam Master Plan on Information Technology.
According to the Vietnam Minister of Information and Communication, the ICT policy of Vietnam involves the following: (1) strengthening the development and training of telecommunication and information technology human resources until 2020, (2) completing the policies and mechanisms to support startups, (3) deploying 4G technology and developing value- added services, (4) developing e-commerce and improving the effectiveness of state agencies’ operation, (5) heightening the state management efficiency in electronic transactions, and (6) strengthening information security (VietNamNet, 2017).
Vietnam focuses on the promotion of research, innovation, and high technology in different sectors under the National Development Programme Tech 2020 (Toh, 2017). Attention is also placed on biotechnology, automation technology, and materials technology as these technologies converge in certain applications with ICT. The following sectors are some of those that will benefit: industry and services, agriculture, healthcare, environment, and security. To make this possible, Vietnam has set as its foundation the development of the technical infrastructure and human resources for ICT.
A variety of programs exist in Vietnam that aims to develop the ICT sector further. One of these is the Payment System and Bank Modernization Project, which aims to digitalize several operations in banks as well as propel the financial industry forward through technology to make it easier to use and increase accessibility for clients, including small businesses. Another is the tax administration modernization project, which aims to utilize technology-based tax administration systems and upgrade the current state of taxation in the Vietnam government (World Bank, 2015; World Bank, 2012; Ministry of Information and Communications, 2009).
Indonesia. The Oxford Business Group (2016) shows that Indonesia is “in the midst of national transformation in the ICT sector. For the past 10 years, there have been advancements in availability of telecommunications across the country, technology awareness and usage, investment in digital infrastructure by the government and private sectors, regulatory oversight, and development planning. These were made possible by the increasing demand of ICT products and services in Indonesia’s business community.
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There are, however, still issues in Indonesia’s ICT sector including infrastructure gap, low information literacy, inefficient “spectrum frequency use”, expensive broadband service, cybercrime, and non-connected government network (Ministry of Communication and Information Technology Republic of Indonesia, 2015).
There are many ICT policies in Indonesia that help make the development of the ICT sector possible. One of these is the National Long-term Development Plan which aims to “strengthen national connectivity to balance economy and infrastructure development”. In the National Midterm Plan 2015 – 2019, Indonesia detailed out several policy directions: increase broadband coverage, enable high speed internet access, optimize spectrum frequency use, and connect the ICT government network.
To give flesh to these policies and plans, Indonesia has implemented several public-private partnerships, private projects, and public projects. One of its key ICT programs and applications include the e-Government agenda, which include a range of initiatives such as the following: e- Procurement, government one-stop services for business registration, siMAYA (virtual office administration system), Indonesia National Single Window (e-payment, e-licensing, e-tax, e-port, and e-customs services), online tax (all payments made via banking or postal systems), central e- learning portal (broken down into primary, secondary, and higher education), electronic identity card for all Indonesian citizens (was previously used as the voter database for the 2014 elections), and social welfare smart cards (cards for basic health insurance, basic education, and social welfare services) (Tabor and Yoon, 2015).
Indonesia’s ICT sector is growing rapidly. This is partly driven by a young population that are more adept with the use of technology, and who are active users of mobile telephone and internet services. However, Indonesia still lags behind, at least in the Asia-Pacific, in terms of broadband access. Large areas in Indonesia have limited access to internet connection, and this slows down ICT development for e-learning, telemedicine, and other public programs. The government has attempted to bring ICT facilities to these areas, but progress has been slow. Overall, Thailand, Philippines, Vietnam, and Indonesia are on their transition towards an innovation and knowledge-based economy given their current set of policies and programs. However, several issues must be addressed, including the need to develop further these countries’ ICT infrastructure, to enhance nationwide broadband access, and to improve the information literacy among their people.
Nascent, high potential ICT development: Cambodia, Myanmar, Lao PDR
Cambodia. Cambodia is in the process of developing ICT policies and frameworks. Among its main goals apart from developing policies and frameworks include addressing structural challenges and enhance the business and investment environment in the ICT sector, and providing measures and interventions where needed (Yousos, 2017).
Cambodia’s ICT Policy Department detailed down a set of objectives for them to be able to develop their ICT sector. Among these include improving and expanding telecommunications infrastructure and usage, developing ICT skills of its people, diversifying the ICT industry, and promoting ICT applications.
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They are also in the process of developing policy and regulatory frameworks in line with broadband, radio communication, e-Government initiative, e-commerce, cybercrime, digital signatures, protection of women and children online, and other ICT-related policies and regulations. These are encapsulated in Cambodia’s National Information and Communication Technology Policy that will build on existing government initiatives and overcome the lag of ICT development in the country (Yousos, 2017; Japan International Cooperation Agency, 2015).
Under the Cambodian ICT Masterplan 2020, four key points are addressed to tackle the lack of development in the country’s ICT sector: empowering people, ensuring connectivity, enhancing capabilities, and enriching e-Services (Korea International Cooperation Agency, 2014). As the country is still in the nascent stages of ICT development, more opportunities for international collaboration abound, as well as technology exchange and transfer.
One of the main projects of the Cambodian government is on e-Commerce, which the Cambodians define as “commercial activities via electronic communication.” The Cambodian government is rolling out programs for e-commerce promotion focusing on establishing a technical foundation, implementing direct and indirect administrative support, enhancing the legislative environment, and executing flagship projects under e-commerce.
Apart from e-commerce, other flagship projects of the Cambodian government are the development of an e-Government initiative, ICT security, the setting up of a tourism network, and the enhancement of educational programs. These projects will have ICT at its center, thereby enabling several opportunities including the optimization of processes and increased attractiveness of their country among foreign investments.
Myanmar. Myanmar has been keen on the development of ICT, which is why several policy frameworks on the sector have been formed: Framework for Economic and Social Reform 2012–2015, ICT Masterplan 2011–2015, Telecommunications Masterplan, and E-Governance Masterplan. Among the key elements of these frameworks are the creation of an IT-intelligent society, reduction of the digital divide, widespread applications of IT to improve the educational levels in the population, and many others. These frameworks are also implemented by several Myanmar authorities, including the Myanmar Posts and Telecommunications Enterprise, which provide different kinds of telecommunications services.
It was in 1996 when the Computer Science Development Law was formed that the ICT sector of Myanmar began its revamp. The law lays down policies and regulations to promote and disseminate the usage of computer and science technologies in various sectors (Crossroads, 2013). Meanwhile, some issues in Myanmar’s ICT development include infrastructure, government support, technology transfer, international exposure, quality assurance, legal frameworks, standardization, and business practices. The ICT sector in Myanmar, therefore, is still at its nascent stages. Several opportunities are available in the ICT sector both for government and public sectors.
Currently, Myanmar’s ICT market is dominated by hardware, followed by training and software, and other services such as trading, web and internet, network, and maintenance. One of the key drivers of ICT development are software-related businesses. With the construction of the
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Myanmar ICT Park in 2002, the software industry led the growth of the ICT sector (SEACOOP, 2010).
One of the key projects of Myanmar is the e-Government initiative, despite consistently being ranked as one of the least developed countries in e-governance. The e-Government initiative is perceived by the Myanmar government as “good government and clean governance,” apart from just increased efficiency. Moreover, the government is working closely with the Korean International Cooperation Agency in developing e-government platforms and in integrating ICT in policy formulation and legislation. Apart from these, Myanmar is also rolling out private and public initiatives in telecommunications, software, education, and mobile banking, among others.
Lao PDR. Lao PDR’s ICT development is at its nascent stages, with the government establishing frameworks and policies to further grow the sector. The Lao government has identified nine priorities in line with the development of their ICT sector: infrastructure and access, enterprise and industry, research and development, applications, human resource development, legal framework, awareness, poverty alleviation, and standardization and localization (SEACOOP, 2010). The priorities are comprehensive and attempt to set the foundations to maximize the entry of ICT in the country.
Several policies and regulations have been rolled out by Lao PDR to improve its ICT sector. These include the National ICT Policy 2015 – 2025, National Broadband Plan 2012 – 2020, and e-Government Master Plan 2013 – 2020 (Phissamay, 2016).
The main ICT program of Lao PDR is the e-Government Project. This project is divided into four parts which includes infrastructure, e-applications, human resource development, and providing ICT facilities (SEACOOP, 2010). The infrastructure component focuses on building internet connections through the fiber optic data centers and ministries in order to improve information and knowledge exchange. The e-applications contain seven key applications such as e-portal, e-document, e-archive, e-Map, e-Registration, e-Learning, and video conferencing. The human resources development training aims to improve the ICT skills and knowledge of its people. Lastly, the provision of ICT facilities such as servers, desktops, printers, photocopies, and video conferencing equipment to various ministries enable the full usage of the e-applications project.
Cambodia, Myanmar, and Lao PDR are at their nascent stages in ICT development. Among the issues that these countries need to address alongside developments in ICT policies and programs are the lack of ICT infrastructure, government support, technology transfer, international exposure, quality assurance, legal frameworks, standardization, and business practices.
Conclusion
The policies and programs being rolled out by the respective governments of the 10 ASEAN member states are expected to improve the ICT sector for the general ASEAN population. While countries like Singapore and Malaysia have undergone a rapid transformation of their ICT sectors through infrastructure development, other countries are still at their nascent stages in ICT and are beginning to learn the topes. One of the possible directions to address this digital divide is the exchange of knowledge and experiences in terms of ICT policy formulation. Events ranging
47 | P a g e www.paomassociation.wordpress.com from competitions and expositions, for instance, can help policy makers and other key stakeholders gain a better understanding of the existing ICT landscape in the region. These can help them benchmark and to adopt innovations in their respective ICT sectors.
Overall, these developments augur well for the region’s businesses, including SMEs, as they address two major factors that, according to the ASEAN SME Policy Index 2014, hinder the adoption of ICT among business: (1) the lack of ICT facilities, and (2) the perception of high risks and costs of adoption. With policies and regulatory regimes set in place, governments can now speed up investments in infrastructure needed consistent with their national priorities, whether these are to build a knowledge-based digital economy, to reduce corruption and bureaucracy in government, to support local businesses, or to promote social equity.
Once the infrastructure is in place, coupled with investments in human resource development, this opens up opportunities for businesses to take advantage of various ICT tools and skills such as the Internet of Things, which involve the use of sensors to track down essential components of business data; technopreneurship, which involves the merging of entrepreneurship and creative usage of technology in businesses; open data, which refers to the transparency of data online such as relevant government data; and big data analytics, which is redefining the way we process big amounts of data from day-to-day business transactions. These technologies, coupled with the digital competence of a new generation of ASEAN citizens, pave the way for SMEs in the region to thrive and to grow.
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National Academy of Science and Technology. (2014). Forum on ICT infrastructure: Plans and strategies for national development. Retrieved from http://www.nast.ph National Electronics and Computer Technology Center, National Science and Technology Development Agency, and Ministry of Science and Technology. (2011). Thailand Information and Communication Technology Policy Framework (2011 – 2020). Retrieved from http://www.mdes.go.th/assets/portals/10/files/e- Publication/Executive%20Summary%20ICT2020.pdf Oxford Business Group. (2017). Indonesia ICT Research & Analysis 2017. Retrieved from https://oxfordbusinessgroup.com/indonesia-2017/ict Phissamay, P. (2016, October 23-29). ICT policy and development in Laos [PowerPoint presentation]. Retrieved from http://www.cicc.or.jp Smart Nation and Digital Government Office. (2018). Smart Nation. Retrieved from https://www.smartnation.sg/about/Smart-Nation Tabor, S. & Yoon, S. Y. (2015). Promoting information and communications technology in Indonesia. Mandaluyong, Philippines: Asian Development Bank. Toh, C. (2016, January 28). Vietnam’s national development programme sets Tech 2020 Plan. OpenGov Asia. Retrieved from https://www.opengovasia.com SEACOOP. (2010). ICT policies, programs, and research priorities in the 10 ASEAN countries. Retrieved from http://workspace.unpan.org United States Department of Commerce. (2017, July 13). Philippines—Information and Communications Technology [Blog post]. Retrieved from https://www.export.gov/article?id=Philippines-Information-and-Communications- Technology United States Department of Commerce. (2017, June 18). Malaysia—Information and Communications Technology [Blog post]. Retrieved from https://www.export.gov VietnamNet Bridge. (2017, March 20). Vietnam needs to promote ICT to grab opportunities for development: Minister. Retrieved from http://english.vietnamnet.vn/fms/science- it/174875/vietnam-needs-to-promote-ict-to-grab-opportunities-for-development--- minister.html Wongwuttiwat, J. & Lawanna, A. (2018). The digital Thailand strategy and the ASEAN community. E J Info Sys Dev Countries. DOI: https://doi.org/10.1002/isd2.12024 World Bank. (2012). Vietnam - Second Payment System and Bank Modernization Project (English). Washington, DC: World Bank Group. Retrieved from http://documents.worldbank.org/curated/en/705761474490058846/Vietnam-Second- Payment-System-And-Bank-Modernization-Project World Bank. (2015). Vietnam - Tax Administration Modernization Project (English). Washington, D.C. : World Bank Group. Retrieved from http://documents.worldbank.org/curated/en/175691468187766970/Vietnam-Tax- Administration-Modernization-Project Yousos, T. (2017, February 1). Telecommunications and ICT development policy [PowerPoint presentation]. Retrieved from http://www.cicc.or.jp/japanese/kouenkai/pdf_ppt/pastfile/h28/170201-3MPTC.pdf
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Determinants of mobile money adoption: Evidence from urban Philippines
Aristotle Manuel D. Go Palawan State University [email protected]
Abstract
This paper aims to investigate factors that drive behavioral intention to adopt mobile money services in Metro Manila, the largest urban region in the Philippines where active mobile and internet users are present. Mobile money is viewed as an enabler for financial inclusion by providing access to financial services to the unbanked and is hinted as a catalyst for financial inclusion in developing economies because of its ability to reach millions of financially excluded within a relatively short space of time. With mobile connections that exceed the country’s population, there is a huge potential to utilize mobile technology and internet to connect unbanked Filipinos to the formal financial system. Multiple regression analysis was used to estimate the determinants of behavioral intention to adopt mobile money using an adapted model. Results show that among the variables, perceived usefulness, facilitating conditions, perceived risk, and perceived financial cost are significant determinants of mobile money adoption. Findings underscore the importance of customer awareness about the potential benefits of using mobile money, and the need to strengthen communications on how it provides additional value and greater convenience in performing financial transactions.
Key Words: mobile money adoption, financial inclusion, behavioral intention
Introduction
Philippines has been cited in several studies as the first country to launch mobile money as early as 2003 (Tobbin, 2011; Bampoe, 2015). Nearly two decades after its introduction, limited scholarly works have been done related to mobile money acceptance, adoption, and its use. Studies and reports from practitioners seem to dominate this phenomenon of interest.
Mobile money is a form of electronic money (e-money) not connected with a bank account or traditional banking system that can be used or transferred using a mobile device. An essential element that distinguishes mobile money from mobile banking, mobile payment, and mobile money transfer is the idea of banking the unbanked. Tobbin (2011) proposed a definition that includes the unique feature of mobile money to deliver a wide range of financial services to the unbanked using mobile device. Mobile money services include (1) person-to-person (P2P) transfer of funds that includes both local and international remittances, (2) person-to-business (P2B) payments for payment of goods and services, and (3) mobile banking functions that include payments for bills, loans, and select government transactions, and deposit and/or withdrawal of funds (Donner, 2008). Recent additions to mobile money services are micro-insurance, micro-
51 | P a g e www.paomassociation.wordpress.com credit, and investments. Thus, making mobile money one of the most interesting innovations in financial services as it combines mobile phones and internet to perform a wide range of financial transactions. Mobile money can turn a mobile device into a business tool that either complements or substitutes banks, ATMs and credit cards (Ventakesh, Morris, Davis, & Davis, 2003).
Mobile money is viewed as an enabler for financial inclusion by providing access to financial services to the unbanked. It is hinted as a catalyst for financial inclusion in developing economies because of its ability to reach millions who were earlier (financially) excluded within a relatively short space of time and helping millions to perform financial transactions in a relatively cheap, reliable and secure way (Mutsonziwa & Maposa, 2016). Mobile money platforms are of interest to the base of the pyramid (BoP) community because of the potential to connect millions of poor and “unbanked" people to the formal financial system (Balasubramanian & Drake, 2016). Global Financial Inclusion Database shows that a significant decrease of the unbanked population in several countries from 2011 to 2014 can be attributed to mobile money. It is believed that increasing financial inclusion leads to an improvement in the lives of people from the low-income groups. Financial inclusion is considered as a critical element that makes growth inclusive as access to finance can enable economic agents to participate in productive activities, cope with unexpected short-term shocks, and make longer-term consumption and investment decisions (Park & Mercado, 2015).
Financial inclusion as envisioned by The Center for Financial Inclusion is “a state in which all people who can use them have access to a suite of quality financial services, provided at affordable prices, in a convenient manner, and with dignity for the clients.” However, about 2 billion adults in the world have no formal account. Thus, sending money to the family by a remote worker is quite expensive for financially excluded people (Carro & Sanchez, 2017). In a study conducted in the Philippines in the year 2009, about Php195.00 is spent to send and receive a remittance of Php2,000.00 through remittance center while about Php25.00 is spent to send and receive a remittance of the same amount using mobile money service. Thus, both the sender and the receiver can collectively save about Php170.00 if each of them will spend Php2.50 for SMS fee and cash out fee equivalent to 1% of the remittance amount (Alampay & Bala, 2009).
Based on the first-ever large-sample quantitative assessment of the expansion of mobile money conducted by Groupe Speciale Mobile Association (GSMA) in partnership with Harvard Business School professor, Shawn Cole, and the Director of DFS Lab at Caribou Digital, Jake Kendall, success of mobile money services in developing countries is greater compared with developed countries. In addition to having an enabling regulation, their analysis provides common factors associated with success of mobile money services such as (1) greater probability that mobile money service would grow considerably in countries with high levels of population density; (2) greater success of mobile money in developing countries or countries with low per capita GDP; and (3) greater success in countries with medium levels of account ownership. Philippines has an estimated population density of 337 persons per square kilometer based on the 2015 Philippine Statistics Authority (PSA) data. Based on World Bank rankings, it is currently 37th in terms of population density, 60th in terms of per capita GDP, and per capita GDP ranking that is lower than African countries where mobile money services were successfully deployed. Hence, it is noteworthy to undertake a study on mobile money services adoption in the Philippine context.
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Similar studies conducted recently also support the argument by Alampay, et al. (2009) that mobile phone banking and other technologies substantially reduce the costs that banks and microfinance institutions (MFIs) charge in providing financial services to low-income populations. With much lower costs and more convenient services, formal financial services delivered through innovative means such as mobile money become more attractive to poor people than the informal financial services which are costlier and less secured (CGAP, 2009). Since mobile money can substantially reduce remittance fees, it is considered as one of the tools to further financial inclusion in areas without formal financial institutions.
2014 Global Findex database defines account ownership or being financially included as having an account either at a financial institution or through a mobile money provider. The first type includes accounts with a bank or any other formal institution such as credit union, cooperative, or microfinance institution. The second type includes bank-led or telecommunications-led and mobile phone-based financial services. The typical approach of mobile money service in the Philippines is telecommunications-centric and non-bank approach where a telecommunications company (telco) has a subsidiary that operates the mobile money business.
Top reasons cited in the literature for lack of access to financial services include cost of opening and maintaining an account, travel distance to access points, lack of proper identification documents, and amount of paperwork involved in opening an account. These problems can be addressed by non-traditional financial services such as mobile money because subscribers are not required to travel and set-up an account in a brick-and-mortar branch before they can use the service for payments and certain transactions. Verification of identity or KYC (know-your- customer) process is only required for money transfers.
Based on the latest BSP financial inclusion dashboard, there are about 119.1 million mobile connections and 113% sim penetration rate in the Philippines. However, there are only 11.4 million registered mobile money subscriptions and only 7.0 million among registered are active. Mobile money is viewed as a game-changer and an enabler for financial inclusion by providing access to financial services in unbanked areas. It plays a role in 11 of the 17 United Nations Sustainable Development Goals (SDGs). The best evidence of mobile money benefits on financial inclusion comes from Kenya in Sub-Saharan Africa where it has lifted an estimated 2% of the population out of extreme poverty. It has improved the welfare of people by having a positive impact on household income and helped them escape extreme poverty. Further, over 180,000 women were able to expand their work-related choices and move from farming to business. It was found that households with access to mobile money were better able than those without access to manage negative shocks such as job loss, death of livestock, or problems with harvests. These claims are supported by another study that mobile money users were often able to fully absorb the shocks because they received more remittances and lost less to transaction costs (Suri & Jack, 2011). These findings addressed SDG 1 which aims to end poverty and SDG 5 which aims to achieve gender equality.
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Problem Statement
The deployment of mobile money services in developing economies has mixed responses because consumers’ reactions vary from one market to another. Philippines was among the first to launch mobile money in 2000 and rolled out the services in 2003. However, 2017 data from BSP shows that less than 10% of the population has adopted mobile money as there are about 11.4 million registered e-money account and around 7 million among registered are active. These data prove that the country’s adoption rate is not comparable with other emerging economies with an adoption rate that exceeds 40% of the population such as Kenya. Compared with Kenya, Philippines has considerable domestic and international remittance flows and has more remittance centers. BSP data as of the first quarter of 2018 shows that there are 16,582 pawnshops in the country, and 2017 Overseas Filipino Workers (OFWs) remittances reached USD28.1 billion through non-mobile money transfer offerings. With the current mobile money adoption rate of less than 10% in the country, BSP seems far from its target that by the year 2020 predominantly traditional transactions will be substituted by largely digital financial transactions through its cash- lite program or less cash program. Therefore, this study aims to identify specific factors that influence customers’ intention to adopt mobile money services in Urban Philippines. Knowing these factors may help explain the low adoption rate of mobile money in the country.
Research Objectives
This paper intends to further investigate the key factors that influence consumer’s intention to adopt mobile money services by using key determinants from technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT).
Significance of the Study
The results of this study could further explain some important issues related to customer intentions towards mobile money services in the Philippines. The findings of this paper may assist mobile money operators to customize mobile money products and services to further enhance mobile money user experience.
Scope and Limitations
This study is focused on mobile money services adoption factors such as perceived usefulness, perceived ease of use, facilitating conditions, perceived risk, attractiveness of alternatives, and perceived financial cost. Survey respondents of this study are limited to a certain demographic population of employed and educated in an urban region because the surveys were done in a seminar hall of a professional organization and in a university. Metro Manila is chosen as a research locale based on FinAccess surveys microlevel data between 2006 and 2009 that indicate frequent mobile money users, specifically M-PESA in Kenya, are more likely urban, educated, and well-off (Mbiti & Weil, 2011). While it is highly likely that a large group of active mobile and internet users is from Metro Manila, it may still be unintelligible to generalize from the results of this study.
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Framework
Previous studies on adoption and diffusion of innovations like mobile money were explored and examined using innovation diffusion theory (IDT), technology acceptance model (TAM), and unified theory of acceptance and use of technology (UTAUT) because of theoretical foundations they provide for factors that either encourage or impede the acceptance and use of a technology.
Innovation diffusion theory (IDT) or also known as diffusion of innovations theory (DoI) was introduced by Rogers in 1983 and has been used in previous studies to describe the acceptance of information systems, and to understand new product adoption and diffusion. IDT argues that potential users make decisions to adopt or reject an innovation based on beliefs that they form about the innovation (Agarwal, 2000). IDT describes the adoption of innovation patterns and explains its dynamics. It suggests that the initial adoption of technology begins with innovators and early adopters. IDT also assists to predict if an invention will succeed and how it will succeed. Metropolitan areas are deemed appropriate for studies related to innovations because it is a place where its potential and early adapters have considerable options to use the innovation.
Technology acceptance model (TAM) is an information systems model initially proposed by Davis in 1986. TAM was further developed in 1989 and has been used in various studies that explore factors that affect an individual’s use of new technology. TAM is a widely used, validated and replicated theoretical model in predicting future consumer behavior. TAM suggests that perceived usefulness and perceived ease of use by individuals affect their behavioral intention to adopt or use a system. The slow uptake of mobile money service in the Philippines compared to other developing economies implies a difference in technology adoption behavior. Further, the acceptance of mobile devices to store value and the acceptance of electronic money as a means of exchange depend on consumers’ behavioral intention towards the adoption of mobile money. Being an adaptation of Fishbein and Ajzen’s theory of reasoned action (TRA), TAM is deemed relevant for the conceptual framework of this study because TRA argues that behavior has a direct influence on behavioral intention.
UTAUT is a unified model developed by Ventakesh et al. (2003) and has four determinants of intention and usage: facilitating conditions, social influence, performance expectancy, and effort expectancy. UTAUT is considered a powerful technology acceptance theory that explains consumer intention to use an information system and subsequent consumer usage behavior as it consolidates different models that include TAM and IDT.
Neuman (2006) claims that surveys are appropriate for research questions about self- reported beliefs or behaviors, and therefore ask respondents about their beliefs, opinions, characteristics, and behaviors associated with a phenomenon. The survey questionnaire used in this paper is adopted from a study by Mukherjee in 2015. It was developed through an exploratory survey conducted with industry experts in addition to a comprehensive survey of existing literature. The following specific variables were identified to examine what factors influence the intention to adopt mobile money services in Metro Manila:
Perceived usefulness. Defined as the degree to which a person believes that using a particular system would enhance his or her job performance (Davis, 1989). Davis argues that the
55 | P a g e www.paomassociation.wordpress.com intention to adopt technology is based on behavioral intention which is determined by two beliefs: perceived usefulness and perceived ease of use.
Perceived ease of use. Defined by Davis (1989) as the degree to which a person believes that using a particular system would be free from effort. A new system is likely to be adopted if it requires lesser effort to operate. When a system is complex its use takes a while to be adopted (Rogers, 2003). Perceived ease of use is a key determinant of consumer behavioral intention (Venkatesh et al., 2003).
Facilitating conditions. This refers to the degree to which an individual believes that an organizational and technical infrastructure exists to support technology use (Ventakesh et al., 2003). In this study, this means that mobile money is widely accepted by various merchants to pay for goods and services, pay bills, deposit or withdraw funds, and perform money transfers with ease.
Perceived risk. Identified as a barrier to the usage of any system and was hypothesized to impact the intention to use mobile money negatively (Mallat, 2007). There are six types of perceived risk: financial, privacy, physical, performance, social, and time-loss (Jacoby & Kaplan, 1972). Further, dimensions of perceived risk may vary by product (or service) class (Featherman & Pavlou, 2003). The adopted questionnaire used in this paper is focused on financial risk and privacy risk.
Attractiveness of alternatives. This refers to the perception of how effective the alternatives were in comparison with a service. Innovation is described by Rogers (2003) as an idea, practice, or object that is perceived as new by an individual or another unit of adoption. Rogers (2003) projected characteristics of an innovation that impacts behavioral intention of customers that include relative advantage which he described as the degree to which an innovation is perceived to be better than its predecessor. Consumer acceptance of innovation often includes a decision to choose between maintaining the status quo and deviating from the status quo. Thus, in a qualitative study that explored consumer adoption by Mallat mobile payment was compared with conventional forms of payments such as cash, debit cards, and credit cards. Generally, credible alternatives are expected to have a negative impact on behavioral intention to adopt mobile money.
Perceived financial cost. This refers to the extent to which a person believes that using mobile financial services will cost a certain amount of money. Perception about cost was especially important for consumers in developing countries because services may be perceived as useful but the cost might act as a prohibitive factor to adopt the services (Mukherjee, 2015). Luarn and Lin (2005) empirically identified perceived financial cost as a negative effect on behavioral intention to use mobile banking. Further, perceived financial cost was listed as an important predictor of m- payments usage (Zmijewska, Lawrence, & Steele, 2004).
Behavioral intention. Defined as a cognitive decision-making process to perform a behavior or action (Das & Pal, 2011). It is considered a direct determinant of a prospective user’s technology or system usage and a necessary precursor to the actual behavior (Fishbein & Ajzen, 1975). In the context of this study, behavioral intention is a four-item construct that is measured using a five- point Likert scale.
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Six independent variables and one dependent variable were assessed using a 27-item questionnaire. These 27 items were coded into seven different variables to represent six independent variables and one dependent variable.
Figure 1. Conceptual framework
Hypotheses
The following hypotheses were tested empirically:
H1: Perceived usefulness has positive impact on behavioral intention to use mobile money
H2: Perceived ease of use has positive impact on behavioral intention to use mobile money
H3: The presence of facilitating conditions has positive impact on behavioral intention to use mobile money
H4: Perceived risk has negative impact on behavioral intention to use mobile money
H5: Attractiveness of alternatives has negative impact on behavioral intention to use mobile money
H6: High perceived financial cost has negative impact on behavioral intention to use mobile money
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Methodology
Substantial proportion of money transfers took place in urban areas and centers of commerce. It is typical for a breadwinner to live and work in Manila or another urban center, and regularly send money back to family in another province (GSMA, 2016). This practice contributed to a large domestic remittance market and growth of remittance agents in the country. This study is set in Metro Manila, a region where there is a large group of active mobile and internet users who are more likely at ease with technology and more adaptive to modernization. Previous study shows that the likelihood of owning an account is higher among urban, educated, employed, richer, older, and married individuals while gender does not exhibit a statistically significant association with account ownership (Allen, Demirguc-Kunt, Klapper, Martinez, 2016). Further, technology use is more prevalent in urban areas than those in provincial areas.
In addition to previous studies cited in the scope and limitations section, it is common in the Philippines that some household members work in urban areas and send remittances to family members in rural areas. In a study conducted by GSMA in Tanzania, typical mobile money users are migrant workers sending money home, parents sending money to their children, young adults supporting their parents, spouses supporting their family, and family members sending gifts. Thus, the demand for mobile financial services in urban areas appears to be one of the drivers for adoption. For these reasons, Metro Manila is chosen as the research locale.
Individual-level data were collected through utilizing a survey questionnaire adapted from a previous study conducted in India. Neuman (2006) suggest that surveys are appropriate for research questions about self-reported beliefs or behaviors. Thus, cross-sectional survey may be done when examining respondents’ beliefs, opinions, and behavior related to a phenomenon. Based on the minimum sample size required in typical marketing research as cited by Wong (2013) when six arrows pointing at a latent variable in the model, minimum sample size is 75. Conventional marketing research study would have a significance level of 5%, statistical power of 80%, and minimum R-squared values of 0.25. The minimum sample size required using this parameter from suggested guidelines by Marcoulides and Saunders (2006) depends on the maximum number of arrows pointing at a latent variable as specified in the structural equation model. Given that this study investigates six independent variables pointing to one dependent variable were used in this study, the sample size must be at least 75.
The survey instrument used in the study was designed using inputs from literature to ensure construct validity. Five-point Likert scale was used to capture answers of the respondents on a scale from 1 to 5 (from Strongly Disagree to Strongly Agree).
Multiple regression analysis is used to estimate the determinants of behavioral intention to adopt mobile money services. Jamovi statistical software was utilized for regression, normality tests and collinearity statistics while SMART-PLS was used for validity tests. Using an adapted questionnaire from a previous study by Mukherjee in 2015, six relevant predictor variables of behavioral intention were identified. A model that attempts to explain how these variables influence intention to adopt mobile money emanated from theories in a comprehensive literature review.
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To ensure the validity of questions, a pretest of the questionnaire was conducted prior to the distribution of paper and online surveys for data gathering from people currently staying, studying or working in Metro Manila. The questionnaire was distributed to potential mobile money users who may or may have not adopted the services so far. Google forms was used for online survey while printed version of the questionnaire was administered in a training center for professionals. Online and paper surveys were consolidated to ensure consistency. After incomplete responses were rejected, 171 valid responses were used for data analysis. Cronbach’s alpha was applied to ensure scale reliability.
Philippines has commonalities with other countries that successfully rolled out mobile money where some household members work in urban areas and send remittances to their family members who live in rural areas. Two-thirds of the Filipino population lives in a handful of urbanized areas. Though money flows in both directions between urban and rural areas, it is typical for a breadwinner to live and work in Manila (or another urban center), and regularly send money back to family in another province (CGAP, 2016). Further, students who study in urban areas receive financial support from rural areas.
Results
The respondents include 59 males and 112 females. 70 out of 171 respondents are mobile money users while 101 are non-users. 8 respondents were 20 years old and below, 73 people from 21 to 30 age group, 53 people from 31 to 40, 21 people from 41 to 50, and 8 people from 51 to 60, and 2 respondents from above 60 years old, while 6 respondents did not reveal their age. In terms of highest educational attainment, 128 respondents have completed college, 35 have at least reached postgraduate level, 4 have some college, 2 have completed high school, and 2 have some high school. 128 respondents are employed, 26 are self-employed, 9 are students, 5 are unemployed and currently job searching, and 3 are unemployed and doing housework.
Table 1 Construct Reliability and Validity Cronbach’s Composite Ave Variance alpha Reliability Extracted Attractiveness of alternatives 0.839 0.925 0.861 Behavioral intention 0.924 0.946 0.814 Facilitating conditions 0.840 0.893 0.676 Perceived ease of use 0.919 0.942 0.803 Perceived financial cost 0.925 0.952 0.869 Perceived risk 0.916 0.941 0.799 Perceived usefulness 0.936 0.954 0.839
All constructs are valid measures of their respective constructs on their parameter estimation and statistical significance when composite reliability (CR) values for items scoring are >0.8 (Hair, 2018). The average variance extracted (AVE) are >0.5 justifying the validity of the construct used in the measurement. Items with an outer loading less than 0.7 were removed from 59 | P a g e www.paomassociation.wordpress.com items to be used to measure Attractiveness to Alternatives. Generally, indicators with outer loadings between 0.40 and 0.70 should be considered for removal from the scale only when deleting the indicator leads to an increase in the composite reliability (Bagozzi, Yi, & Philipps, 1991; Hair, Sarstedt, Ringle, & Mena, 2012). Variance Inflation Factors (VIFs) were calculated to detect the presence of multicollinearity between predictors. Collinearity statistics show that variance inflation factors (VIFs) of independent variables range from 1.08 to 2.10, far below the threshold value of 10. All predictors in the regression model with VIFs less than 10 imply that there is no violation of multicolinearity assumption. Further, Shapiro-Wilk tests were conducted to determine whether the distributions of variables were significantly different from normality based on an alpha of 0.05. Perceived usefulness (W = 0.83, p < .001), Perceived ease of use (W = 0.86, p < .001), Perceived risk (W = 0.96, p < .001), Facilitating conditions (W = 0.96, p < .001), Attractiveness of alternatives (W = 0.86, p < .001), Perceived financial cost (W = 0.93, p < .001), and Behavioral intention (W = 0.97, p < .001). The assumption of normality was assessed by plotting the quantiles of the model residuals against the quantiles of a Chi-square distribution, also called a Q-Q scatterplot (DeCarlo, 1997). For the assumption of normality to be met, the quantiles of the residuals must not strongly deviate from the theoretical quantiles. Strong deviations could indicate that the parameter estimates are unreliable.
Multiple linear regression analysis was conducted to assess whether the selected independent variables significantly predicted consumer intention to adopt mobile money. Regression results are presented in Table 2.
Table 2 Regression results summary – Behavioral intention as dependent variable Predictor B SE CI β t p (Intercept) -0.25 2.40 [-4.99, 4.49] 0.00 -0.10 .917 Perceived usefulness 0.47 0.13 [0.21, 0.72] 0.29 3.66 < .001*** Perceived ease of use 0.03 0.12 [-0.21, 0.27] 0.02 0.25 .807 Facilitating conditions 0.55 0.08 [0.39, 0.71] 0.44 6.84 < .001*** Perceived risk -0.18 0.06 [-0.30, -0.07] -0.18 -3.14 .002*** Attractiveness of alternatives -0.15 0.10 [-0.35, 0.05] -0.08 -1.50 .137 Perceived financial cost 0.20 0.07 [0.07, 0.33] 0.17 2.97 .003*** Note: The asterisks indicate that the variable is significant at the levels of 1%, 5% and 10% respectively i.e. ***p < 0.01; **p < 0.05; *p < 0.1.
Results show that among the variables, perceived usefulness, facilitating conditions, perceived risk, and perceived financial cost are significant determinants of intention to adopt mobile money services. The results of the linear regression model were significant, F(6,164) = 30.00, p < .001, R2 = 0.52, indicating that approximately 52% of the variance in behavioral intention to adopt mobile money can be explained by perceived usefulness, perceived ease of use, perceived risk, facilitating conditions, attractiveness of alternatives, and perceived financial cost.
Perceived usefulness is significant and has positive impact on behavioral intention (H1), B = 0.47, t(164) = 3.66, p < .001. The perception that mobile money services add value and more
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The presence of facilitating conditions was found to be a significant determinant of intention to use mobile money services among respondents and impacted behavioral intention positively (H3), B = 0.55, t(164) = 6.84, p < .001. This confirmed the previous findings of Mukherjee (2015). Mobile money infrastructure, network effect, extensive service network, and ecosystem would encourage people to use the service (Mukherjee, 2015).
Existing research suggests that perceived risk has a negative impact on intention to adopt mobile money (H4). Results indicate that perceived risk significantly predicts behavioral intention. Thus, H4 is supported. Perceived risk negatively impacts behavioral intention and is significant with B = -0.18, t(164) = -3.14, p = .002.
Perceived financial cost was also found to be significant predictor of behavioral intention, B = 0.20, t(164) = 2.97, p = .003. However, with 0.20 coefficient, it does not support the hypothesis that it impacts behavioral intention negatively (H6). Based on existing literature, the negative impact of perceived financial cost on intention could represent the price sensitivity of users and potential users or their reluctance to pay for mobile money service as an alternative to cash transactions. Perception of cost, risk, low perceived relative advantage, and complexity were the main reasons behind the reluctance to use of mobile banking (Cruz, Neto, Muñoz-Gallego, & Laukkanen, 2010).
Perceived ease of use (PEOU) is expected to influence behavioral intention to adopt mobile money (H2). In a study conducted in Kenya, PEOU is a significant contributor to the use of international mobile money remittance and this is probably driven by already existing user experience of mobile money given its huge success in Kenya (Correia, Ngare, Sindiga, & Otwoma, 2017). Results of this study does not conform with a priori that PEOU affect behavioral intention, B = 0.03, t(164) = 0.25, p = .807. This may be due to the group of respondents who participated in the survey. More than 95% of the participants have at least completed college who are likely at ease and knowledgeable with innovations like mobile money. Thus, respondents seemingly believe that they can use mobile money without the need to exert much effort. Further, the results of a study aimed to understand the characteristics of mobile money users showed that early adopters of technology are younger, novelty seekers, and more likely to have good employment and opinion leadership than late adopters (Tobbin & Adjei, 2012). The demographics of the group of research participants surveyed are similar to the findings of Tobbin and Adjei (2012).
Based on existing literature, attractiveness of alternatives has negative impact on behavioral intention (H5). However, the results of this study do not conform with existing literature. Attractiveness of alternatives did not significantly predict behavioral intention, B = - 0.15, t(164) = -1.50, p = .137. Based on this sample, a one-unit increase in attractiveness of alternatives does not have a significant effect on behavioral intention.
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Conclusion and Recommendations
Findings highlight the need to strengthen communications on how mobile money services provide additional value and greater convenience in remittance transactions, making/receiving payments for goods and services. Perceived usefulness, being one of the significant predictors of behavioral intention, suggests the importance of customer awareness about the potential benefits of using mobile money. Thus, effective marketing communication is important in making the service to be perceived as useful. Further, facilitating conditions also came out as one of the determinants of intention to use mobile money. Thus, expanding service network and acceptance of mobile money by more merchants would likely increase adoption. Further, mobile money operators may consider expanding distribution strategy to have more convenient locations where subscribers may perform cash in/cash out transactions. Perceived financial cost, being a significant variable, may be addressed by service providers by making subscribers consider the overall benefits of using mobile money.
Areas for Future Research
Given that the respondents of this study are limited to a certain demographic population of employed and educated in Metro Manila, it will be interesting to validate potential factors that drive mobile money adoption of residents from other regions in the Philippines in future studies, especially in rural areas. Findings of this study may also differ from findings of studies conducted in other countries because of the difference in sample sizes and social class of respondents. A study that includes a broader demographic profile of respondents may be conducted in the future. Given that this paper used cross-sectional data collected from respondents in a snapshot, responses may be influenced by individual conditions during data gathering. These conditions may also provide significant differences in the findings of this paper. A longitudinal study with better-defined population and sample size that compares the findings of this study with an up to date survey may also be conducted in the future.
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Hair, J., Sarstedt, M., Ringle, C., & Mena, J. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414–433. https://doi.org/10.1007/s11747-011-0261-6 Hair. (2018). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). Los Angeles, CA: Sage Publishing. Jack, W., & Suri, T. (2011). Mobile money: the economics of M-PESA. National Bureau of Economic Research. doi: 10.3386/w16721 Khan, M. R., & Blumenstock, J. (2017). Determinants of mobile money adoption in Pakistan. Proceedings of the NIPS 2017 Workshop on Machine Learning for the Developing World. California, USA. Retrieved from https://arxiv.org/pdf/1712.01081.pdf Luarn, P. and Lin, H.H. (2005). Toward an Understanding of the Behavioral Intention to Use Mobile Banking. Computers in Human Behavior, 21, 873-891. http://dx.doi.org/10.1016/j.chb.2004.03.003 Marcoulides, G. and Saunders, C. (2006). "PLS: A Silver Bullet?," MIS Quarterly, (30: 2). Mbiti, I., & Weil, D. N. (2011). Mobile banking: the impact of M-PESA in Kenya. No. w17129. The National Bureau of Economic Research, doi: 10.3386/w17129 Mukherjee, J. (2015). Mobile money adoption in India: Evidence from early adopters of technology. Vilakshan: The XIMB Journal of Management, 12(2), 95–118. Mutsonziwa, K., & Maposa, O. K. (2016). Mobile money - A catalyst for financial inclusion in developing economies: A case study of Zimbabwe using FinScope survey data. International Journal of Financial Management , 6(3), 45–56. Neuman, W. L. (2006). Qualitative and quantitative research designs. WL Neuman, Social research methods: Qualitative and quantitative approaches (6th ed., pp. 149-178). Boston, MA: Pearson Prentice-Hall. Park, C.-Y., & Mercado, R. V. (2015). Financial inclusion, poverty and income inequality in developing Asia. Manila, Philippines. Asian Development Bank. Retrieved from https://digitalcommons.ilr.cornell.edu/intl/432/ Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: Free Press. Venkatesh, V., Morris, M. G., Davis, G. and Davis, F. (2003) User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3): 425-478 Zmijewska, A., Lawrence, E., Steele, R. (2004). Towards Understanding of Factors Influencing User Acceptance of Mobile Payment Systems. Proceedings of the IADIS International Conference WWW/Internet 2004. Madrid, Spain. Retrieved from http://www.iadisportal.org/digital-library/towards-understanding-of-factors-influencing- user-acceptance-of-mobile-payment-systems January 9, 2020
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A phenomenological analysis on the waste separation behavior and awareness on plastic recovery capability of a barangay in Manila
Ranzelle T. Go, Jana D. Josef, Fabienne Renee V. Panelo, Vincent Anthony V. Uy, and Angelique C. Blasa-Cheng De La Salle University [email protected], [email protected], [email protected], [email protected], [email protected]
Abstract
This research followed an interpretative phenomenological analysis to explore the attitude, practices and behavior of low-income households concerning waste separation of Barangay 852 in Pandacan, Manila. It also examined their current waste management system and households’ awareness and participation in the plastic recovery initiatives of Fast Moving Consumer Good (FMCG) Companies.
Results revealed that while residents were aware and knowledgeable of the concept and practice of separating wastes, they still fail to perform proper and complete waste segregation. The barangay’s current waste management system is also not clearly communicated and weakly implemented, as conflicting perspectives on the processes were documented. Participants also showed little knowledge, awareness and participation in plastic recovery programs of FMCG companies within the barangay. Only Unilever’s Misis Walastik program is the most visible and present among the community members. Deterrents to their waste separation behavior were identified to be due to (1) difficulty to change old habits and inability to form and sustain new desirable habits (discipline); (2) limited knowledge and access to proper and complete waste segregation; (3) lax implementation and monitoring of barangay waste management system and municipal waste collection; and (d) delegation of waste separation responsibilities to others.
Furthermore, this paper asserts that tackling the issue on waste separation at its source (household) in integral, necessary and crucial for any solid waste management or initiatives to convert trash into resources to be effective.
Key Words: waste separation behavior, attitude; awareness of FMCG plastic recover initiatives; waste management system; municipal waste collection; plastic issue
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Introduction
For decades, the solid waste management (SWM) that people have been accustomed to is reduce, reuse, and recycle, and yet, waste management (to minimize or keep it at its lowest level) is still a global challenge. Although overall recycling rates have increased globally, growing population has increased waste generation (Messenger, 2018).
In 2016, National Capital Region (NCR) has posted the greatest volume of wastes, around 9,212.92 tons per day in 2016. In a study by World Bank (2012, as cited in SEPO, 2017 and Messenger, 2018), Philippine municipal solid waste generation per capita per day for the Philippines is expected to generate 77,776 tons of waste per day by 2025.
The Philippines is the third largest plastic polluter, only behind China and Indonesia (Deutsche Welle, 2017). As a sachet economy, the country relies on sachet packaging or more commonly known to Filipinos as tingi-tingi system. The system has been effective in augmenting the budget of low-income households due to their affordable prices as needed, but it has also been generating plastic wastes from packaging of fast-moving consumer goods which are becoming environmental hazards (e.g., flooding) (Posadas, 2014).
Fast moving consumer good (FMCG) companies have already been called out to be held accountable for the waste created and left behind by their products, and they have been urged to implement long-term solutions in which consumers can participate (Deutsche Welle, 2017). However, efforts must not be coming from manufacturers and policy makers alone. Household consumers must be willing to participate to make the environmental programs effective.
Initiatives have failed to produce the desired outcome of managing waste. There has been disconnection between the effectivity of recycling programs and household participation is the fact that they do not know how to segregate or separate their wastes (McAllister, 2015). Before people get to participate in return plastics programs or any other initiative done by companies and the government, it must be established first if those belonging in the low socioeconomic status, the biggest consumers of plastics and sachets, have the knowledge and discipline to segregate their wastes, which the researchers ought to know.
This research focused on low-income households that reside in one community or barangay in Manila because it is the biggest solid waste polluter in the country. Low-income households (monthly family income is below P31,560 per month ) were chosen because they are the biggest players of the sachet economy (Deutsche Welle, 2017; Albert et al., 2015).
To understand why plastic recycling initiatives are ineffective the researchers explored how residents experience waste management and participate from waste generation to waste collection by answering the following research questions:
1. What kind of attitude do people exhibit towards waste separation and how do they separate their wastes? 2. What influences their waste separation behavior and what could encourage them to separate wastes?
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3. How do they perceive the current waste management system and its implementation? 4. What do the households recommend in solving the issue on waste management? 5. How aware are they of the various FMCG programs on plastic waste management?
Conceptual Framework
Figure 1. Proposed conceptual model
The proposed conceptual framework illustrated in Figure 1 made use of concepts designed by Xu and colleagues (2017), while merging it with Rousta’ (2018) research wherein the functional elements in a municipal solid waste management are interrelated; Rousta’s (2018) framework enumerated process from waste generation to waste disposal, but for this study, researchers only considered until collection. The influence of the expanded theory of planned behavior as conceptualized by Xu et al. (2017) can be seen through the concepts of attitude, behavior and intention to separate wastes, subjective norms, perceived behavioral control and perceived policy effectiveness. Following the private sectors’ involvement in solid waste management as proposed in R.A. 9003, this study also explored the households’ awareness of and participation in FMCG initiatives on plastic waste management. There have been many programs implemented by several FMCG companies to recover and recycle plastic waste in partnership with various organizations that also entail consumer participation. Awareness is a consumer’s evaluation of his familiarity of the listed program and its mechanics, while participation is one’s involvement in the said activity or with direct contact in the program.
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Methodology
Research Design and Paradigm
The strategy of inquiry used in the study is an interpretative phenomenological analysis (IPA), which aimed to explore the participants’ experience of waste separation and of the barangay’s current waste management system from their perspective. A constructivist approach was used to encourage participants to share their personal experience, while critical theory was also applied to understand participants’ background and analyze where they are coming from.
IPA specializes in rich discussions and lived experiences, this approach allows the best views in their natural environment. The IPA was utilized to highlight the experience of the leaders of the barangays and some members (who mostly interact) to waste separation behavior and awareness of certain people (in the low-income households) in the programs of the FMCG companies. Based on pilot research before this manuscript, the best way to get rich data will be through heavy interviews in the IPA approach.
Respondents and Sampling Procedures
Barangay 852, Pandacan, Manila, which is composed of at least 500 households, participated in the study. It is composed of 1.24 percent total population in Manila. It was chosen the community for data collection as leaders and members were responsive in sharing its previous and current practices with waste separation and waste management awareness. Moreover, Purposive and snowball sampling were still used with the following criteria set: the respondents must (a) be at least 18 years old, (b) be a Filipino citizen, (c) understand basic conversational Filipino, (d) have an estimated average monthly household income of Php 31, 560 and below, (e) represent one unique household (primary caretaker). No case of two or more respondents representing one and the same household was recorded. The researchers have identified that a household would entail that they have their own gas/electric stove.
Table 1 Demographics of Participants Count Pseudonym Sex Age Occupation 1 Goyo Male 58 Barangay Official 2 Mayumi Female 48 Barangay Official 3 Chedeng Female 35 Barangay Official 4 Jacinto Male 45 Barangay Official 5 Mutya Female 42 Barangay Secretary 6 Claudio Male 58 Market Seller 7 Yasmin Female 48 Teacher 8 Gemma Female 28 Office Employee 9 Amihan Female 35 Sari-Sari Store Owner 10 Irma Female 52 Sari-Sari Store Owner 11 Rodrigo Male 60 Garbage Collector 12 Ramil Male 61 Garbage Collector
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Table 1 enumerates the twelve participants’ profiles whose ages ranged from 28 to 61, with five males and seven females interviewed. Five participants were common barangay members with their own day jobs, while five were barangay officials and the other two were self-employed garbage collectors within the barangay. These three distinctions played a major role in the analysis of the interviews.
Results and Discussion
Waste Separation Behavior, Attitude and Intention
Waste separation is not foreign to the residents of Barangay 852, Pandacan, Manila. Many of the participants expressed that they observe waste disposal and segregation even before the barangay carried out their waste management system. In this regard, barangay officials expected more residents to separate wastes and treat this behavior as common knowledge, especially since they have devised a waste collection scheme that emphasizes the importance of it.
Participants practiced improper and incomplete waste separation. Even though most of the participants perform waste segregation, not everyone does it properly and completely. The researchers noticed that some residents separate their wastes according to their priority, consumption and judgment.
“Yun, kasi diba Pampers. May mga pupu ng bata. Kaya sineseparate namin. The rest, pinagsasama na namin. Kasi hindi naman kami masyadong nagluluto. Bumibili lang kami talaga. So hindi siya talaga, more on Pampers at tsaka mga basura lang na candy-candy. The rest, wala naman. [Pampers (diapers) have child’s feces, which is why we separate them. We mix the rest. Because we seldom cook, we buy food outside. We don’t generate to much waste from food. Pampers (diapers) and small wastes are what we mostly separate.]” (Gemma, 28, Office Worker)
Even if some incorrectly perform waste separation, it has become an everyday routine for most of the participants. There were some who have designated times in a day to manage their wastes. On the other hand, some separate their wastes as soon as they generate them since biodegradable wastes produce a foul odor and may attract insects.
“Tuwing may basura po kami, nagbubukod agad. Diretso na, lalo na yung kapag may nabubulok, tapos agad kasi mamamaho talaga… Kasi siyemre para sa kalusugan namin yun. Kaya talagang kumbaga yung pagtali, saradong sarado, kasi namamaho talaga yung nabubulok. [Every time we have trash, we separate them immediately especially if it is biodegradabe because it spoils easily… And of course, it is for our health. We make sure we seal them by tying them well because biodegradable wastes smell badly.]” (Jacinto, 45, Barangay Official)
When asked about their motivations to separate waste and recycle, they have cited the importance they give to environmental cleanliness and protection, their health and hygiene, as well as the possibility of gaining additional income from it.
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Residents are aware of the current plastic pollution situation in Manila, which is why as much as possible, they would want to contribute to its reduction. Collecting recyclable wastes like plastic bottles and sachets will reduce the risk of it being transferred and improperly disposed of in prohibited areas such as water channels and drainage. Thus, if these will be sorted correctly and reused, there would be no issues anymore with any clogging and flooding.
“Para [sa] kalinisan naman yun [waste separation] e, hindi lang para dito, kahit saang lugar kasi cause yan ng pagbabaha e kaya dapat sa isip nila maging ano, [environmental] sila. [Waste separation is for our cleanliness, not only here, but in other places, as wastes causes flooding, therefore they should think about the environment.]” (Goyo, 58, Barangay Official)
Some residents are well-informed of the detrimental effects of organic wastes to one’s health. These pose a serious threat since the growth of bacteria can lead to infectious and chronic diseases.
“Kasi siyempre para sa kalusugan namin yun. Kaya talagang kumbaga yung pagtali, saradong sarado, kasi namamaho talaga yung nabubulok. [Of course, it is for our health. We make sure we seal them by tying them well because biodegradable wastes smell badly.]” (Jacinto, 45, Barangay Official)
Apart from the intrinsic motivations mentioned, several participants consider the separation and collection of recyclable wastes as a method of gaining additional income. One of the garbage collectors mentioned that he goes over through the plastic bags he collected to check for rubbish and recyclables that can be sold in junkshops. A sari-sari store owner noticed that most of her customers and neighbors would also collect papers, cardboards, tin cans and plastics – anything useful for them and sell them to earn money.
“Kasi ang napapakinabangan nila, binebenta na nila. Yung pwede na nilang itapon, sa basura yun na yung tinatapon nila. [Those that are useful, they sell them. Others that can be disposed of, they throw them away.]” (Mayumi, 48, Barangay Official)
Attitude Towards Waste Separation and Intention.
Residents generally show a positive disposition towards the act of separating wastes. One resident who does not practice waste management properly expressed her intention and willingness to do it correctly this time.
“Maganda nga yun. Yung binubukod. Para din malinis. Kasi diba pagsasama din sa trash can, masyadong madumi. Tapos yung mga amoy, sama sama na. Yung mga pagkain, yung basa, pag sinama mo diba ang baho? Pag pinagsama mo ang panget. Ganun nga. [It is good to separate wastes. It is cleaner. If wastes are mixed in the trash can, they are more dirty. And they produce mixed odor. Food and wet wastes, when mixed together, smells foul right? It’s bad to mix them.]” (Gemma, 28, Office Worker)
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Similarly, the secretary of the barangay shared that their community has the same optimistic mindset towards waste segregation. Even before the local mandate on cleanliness, it has already become a habit for them to clean the streets and corners of the barangay.
Participants in the community have the “Ningas Cogon” mentality. Intention and attitude towards waste separation is not always positive. One of the garbage collectors observed that even if some residents display enthusiasm and dedication at the start to participate in waste management initiatives of the barangay, they return to their old habits of not separating wastes after a week. Government collection agencies act similarly. For some time, they control the types of wastes they collect each day, but as weeks progress after implementation, they became more lenient.
“Dapat nga nakasegregate nga yan eh. Siguro one week lang nakasegregate tapos bumabalik na naman na hindi nakasegregate…. At tsaka ningas kugon lang, Brother. Halimbawa may na implement na na ganoon. Mga 1 week lang siguro mapalie low. Okay na rin sila sa ganun (halo-halo na basura). [Ideally, they should be segregated. Segregation only happens for a week, after that, they go back to not segregating. They are not consistent, brother. For example, there is an implementation. Then after one week, the practice will lie low. It is alright for them to mix (wastes).]” (Rodrigo, 60, Garbage Collector)
Perceived Behavioral Control and Subjective Norm
The participants discussed how important it is to have available resources, support and influence from their family, community and the government for it to be easier for them to perform waste separation.
The ability of residents to perform waste segregation activities is heavily influenced by their available time, space, government facilities and resources, knowledge and convenience. Since most of the participants have daily jobs, they resort to handling their wastes at designated times of the day.
The lack of space for separated wastes in households is also a factor that hinders the residents from segregating. Residents coming from low-income families are unable to provide an allotted space for their wastes inside their homes. Most of them do not have any choice, but to place their plastic bags outside.
“Sa labas lang sinasabit namin kasi yung bahay naming maliit lang, kaya sa labas po nakasabit. [We hang them outside since our house is small.]” (Jacinto, 45, Barangay Official)
When the researchers roamed around the barangay to observe their current waste situation, they found garbage bins for biodegradable and non-biodegradable wastes. However, these are placed hard-to-locate areas and these are not in a good condition anymore. Some of the garbage bins were removed because these were not properly maintained and utilized.
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“Oo, mga separating bins, ang kaso, niligpit namin kasi nga yung mga constituents na iba, inaasa na lamang nila yung basura nila sa amin, sa pagtatapon. At tsaka, minsan yung basura ng bahay nila, doon na rin nila nilalagay. Napakahirap kasi sa aming street sweeper na lahat nang… marami...Meron kasi dito sa gitna, meron din sa kanto… Kaya pinatanggal po namin yung para po yung mga constituents matuto silang magatapon ng sarili nilang basura. At matuto na ring magsegregate. [We have separating bins. However, we removed them because other constituents relied their waste disposal on us. And sometimes, they put their house wastes in our separating bins. It is hard for us street sweepers to attend to many locations… here at the middle or across the street… We removed them so that our constituents will learn to throw their own trash. And to learn how to segregate.]” (Mutya, 42, Barangay Secretary)
In one household, it is consistent that only few members of the family practice waste separation. It is noted that most of them are either the mothers, the head of the households or those who are left to guard their homes.
“Hindi, hindi ako yung nagbubukod yung, asawa, ko kasi siya yung laging nasa bahay. Kasi may trabaho ako. [No, I do not segregate, but my spouse because she is always at home. Because I have a job.]” (Jacinto, 45, Barangay Official)
The housewives are often supported by their husbands in separating wastes. One resident mentioned that it is actually her husband who pushes her to learn how to separate wastes because they can gain something from it.
“Siya nga nagsasabi na “ibukod mo yan kasi mabebenta pa natin yan. Wag mo itapon yan. [He is the one who tells me to separate those because we can still sell them. Do not throw them.]” (Amihan, 28, Sari-Sari Store Owner)
One of the mothers also mentioned that she taught her children to practice waste separation, and she has been gaining support from them ever since. The recyclable wastes they collect are used for their school projects.
Aside from family, one of the barangay officials mentioned that they have been very proactive when it comes to persuading their neighbors and community members to manage their wastes properly. For example, during barangay assemblies, they would often announce the rules and regulations of the barangay on waste management as well as the advantages they will get from doing it. He keeps on reminding them that their wastes should always be properly disposed of and if they see wastes lying around, they should already take initiative to pick these up.
Current Waste Management Program
To further understand the waste management system of the barangay, the researchers asked the participants to illustrate the process of which wastes are collected in their community. During the interview, it was noticed that people started to complain and give criticisms as feedback to the current waste management system.
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The study found conflicting perspectives of the participants. Interestingly, their accounts of how wastes are collected were seemingly in sync only up to the extent of their class or group, while some key information differed from one group to another. Other than the first step in which the barangay announces that wastes are about to be collected in the morning, all the other succeeding steps differ. The researchers synthesized three perspectives on the barangay’s current waste management program and were summarized in Figure 2.
Figure 2. Three perspectives on Barangay 852's current waste management program
Garbage collection were done by different agents. It transpired in the interview that residents have someone collect their garbage in the morning and pay for their services. Although most of them employ the services of the barangay’s appointed garbage collectors, others have their other collecting agents, or they themselves bring their wastes to the collection site.
“Bata lang. Pinapakuha lang namin kasi may pasok kami sa umaga… ‘Yung mga taga- Ilang-Ilang, kabilang barangay… kaso bihira siya kumuha. Minsan after 3 days. [Only children. We ask them to get the wastes because we have work during the morning… Those from Ilang-Ilang, another barangay, also get them… but they seldom collect. Sometimes it takes them three days.]” (Gemma, 28, Office Worker)
Some barangay programs were discontinued. Participants mentioned that large waste bins were once available in every street of the barangay; however, it was discontinued due to some residents throwing their household wastes there when in fact, the bins were supposed to be for wastes found in the streets. Additionally, before, there were streets weepers, but now the barangay officials themselves are the ones cleaning the streets.
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“Inalis na kasi nga kung sino-sino na lang nagtatapon nagkahalo-halo minsan yung nasa ‘yung basura nasa loob ng bahay nilalabas nila. Dapat kasi ang lalagay sa mga basurahan dito yung dito nakalat sa kalsada. [They were removed because random people put their wastes without segregation, and sometimes, they put wastes coming from their houses. The garbage bins are for wastes picked-up from the streets.]” (Jacinto, 45, Barangay Official)
Recommendations from Households
Even though barangays are mandated by the local government to perform waste segregation and proper waste management, some residents still fail to handle their garbage properly and sort their waste accordingly. Participants were asked to recommend how to solve the issues on waste management and persuade community members to separate waste and recycle.
Education plays are role. They mentioned how training community members and having practical seminars can be used as tools to further instruct and guide them on proper waste management, especially because this worked for the youth in their barangay. Previously, an organization named AKAP sa Bata Philippines (AKAP) trained the youth on the basics of waste segregation. Because of AKAP, the children have been cooperating and helping them maintain the cleanliness of their barangay.
“Sa amin kasi ngayon ito ang barangay namin na wala ka masyadong nakikitang kalat kasi ‘yung mga kids namin dito, naging member ng grupong AKAP, sila mismo na-train para malaman nila kung saan nila itatapon yung mga waste nila...nabubulok…naglilinis yung mga bata every Saturday. [Currently in our barangay, you will not see too much litter because our kids became members of AKAP group. They were trained to know where will they throw their biodegradable waste… The kids clean every Saturday.]” (Mutya, 42, Barangay Secretary)
Penalties and incentives can be imposed. The majority of the interview participants conveyed their approval of imposing both rewards and penalties for residents who follow the right practices of waste management and those who do not respectively.
“Parang sa tingin ko, kung mai-implement yung inaano [pinaplano] ni Mayor Isko ngayon, na ‘yung mga basurang mga pwedeng mapakinabangan meron kang points para ipalit mo ng pagkain or ipapalit mo ng mga grocery, bigas o asukal. Baka makatulong pa. [In my opinion, if the plans of Mayor Isko will be implemented, wastes which can still be utilized can be given points to have them exchanged for food or grocery, rice or sugar. This can help.]” (Mayumi, 48, Barangay Official)
However, some interview participants did not see the need to give rewards and incentives. For them, residents should already be motivated by the possible advantages and disadvantages of proper waste management since it is for their own sake.
“Palagay ko, kahit hindi na bigyan reward e kasi para sa kanila na rin ‘yun ‘di ba? [For me, even if there are no rewards, because it is still for their own good, right?]” (Goyo, 58, Barangay Official)
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Some think that imposing penalties or getting fines from people who were not able to separate their wastes could be done. Funds raised from fines may also be used by the barangay for their planned activities.
“Parang lagyan mo na ng multa. Para maging fund din nung barangay. Tsaka para maging lesson din sa mga tao. [It is like we add penalty This can be a fund of the barangay. Also, it will teach the people a lesson.]” (Gemma, 28, Office Worker)
Implementation of Current Waste Management System and Barangay Support should become stricter. The barangay may have an existing waste management system that they follow, but both residents and barangay officials believe that they lack strict implementation. When the program was first implemented, people were following the ordinance on waste separation, but after which, they started to go back to their old habits again, as the garbage truck collectors and resident garbage collectors were getting more lenient with them. Given this, most of them suggested that it would be better if the collecting agents would be stern in collecting the residents’ wastes. They should not accept the wastes given to them if these were not segregated properly.
A barangay official approved of this suggestion; he also deemed it necessary for residents to be informed that the garbage collection agencies or the garbage trucks would not collect their wastes. This could persuade the residents apart from imposing penalties since having garbage piled up and stocked in their homes would be more difficult for them. He also noted that it is important to have the support of both the barangay and community members to make this initiative more plausible.
Plastic Recovery Programs of FMCG Companies
FMCG companies partnered up with the local government of Manila for their plastic reduction and recovery programs. A barangay official mentioned that the residents who are knowledgeable of the Misis Walastik program keep and collect their used sachets, cut it out into small pieces and place it in a sack until it fills up. After the sacks were amassed, these were then given to the barangay representatives and were brought to Sacramento (Unilever’s Plastic Recovery Center) for weighing. The secretary of the barangay, who is their representative for the “Misis Walastik Program,” mentioned that the company weighs and gathers their accumulated plastic wastes every 28th of the month and in return, they receive two bars of laundry soap per kilo. When asked what the company uses these for, the barangay representative divulged that they were informed that the plastic sachets will be hauled over to Unilever and will be converted into chairs or hollow blocks that could be used by schools.
Even if plastic recovery initiatives such as the “Misis Walastik Program,” are widely implemented in the city, some residents remain unfamiliar with them. A barangay official mentioned that there are several sari-sari stores that collect the used sachets purchased by their customers to reap the rewards. However, when surveyed, not all sari-sari store owners were aware that plastic wastes and sachet products can be exchanged for consumer products or rewards of any kind. A resident sari-sari store owner shared that she has not heard about any of these initiatives, and none of her customers return sachets. One of the garbage collectors revealed that even though he knew of such programs through advertisements in television, he observed that these have not
75 | P a g e www.paomassociation.wordpress.com reached their whole barangay and not everyone is knowledgeable about it; hence, not all have taken advantage of the program.
The awareness and knowledge of some residents also did not translate to their participation in such activities. A sari-sari store owner chose not to involve herself in these recovery programs. She does not bother to collect the sachets anymore and gives them directly to those who ask it from her. Her customers also do not return their plastic wastes because they immediately exchange it for load.
“Dito naman wala silang ganun, tinatamad silang mag-ganun. Hindi ako nagkokolekta, kasi pag binili nila, kanila na yun. Sa Surf palit nila ng load, sila na yun. Hindi na nila binabalik…. Ako, yung aking plantsadora, hinihingi tapos kinikilo nila sa Sacramento, hinihingi sakin yung mga foil, kasi tinitimbang yun sa kanila. Kaya binibigay ko na talaga yun. [Here, they do not have that, they are lazy to do that. I do not collect, because when they buy, it is theirs. For Surf, they exchange load by themselves. They do not return them. My housekeeper asks for the foils and have them weighed at Sacramento, which is why I give them away.]” (Mayumi, 48, Barangay Official)
Aside from exchanging sachets with consumer products, some residents sought for alternatives that can easily turn wastes into money. For instance, the garbage collector, after receiving the plastic wastes from the residents, found it easier to just sell these to junk shops across their barangay.
“Kapag may nagbibigay samin ng mga plastic diyan, amin na yun, pera kasi yun eh… [Ibenebenta naming] dito sa may highway lang. Maraming bentahan dito. Sa highway lang meron na diyan, bakal lahat. Titimbangin nila.[When someone gives me plastic wastes, I consider them ours as they mean money… We sell them along the highway. Many shops are located nearby. Along the highway, there are shops, all of them buying metal scraps. They weigh the plastic wastes.]” (Rodrigo, 60, Garbage Collector)
Moreover, one resident opts to reuse his plastic products instead of giving it to plastic recovery programs or selling them to junk shops.
“Hindi kami nangogolekta ng mga resiklong plastic, kasi yung mga Wilkins namin na bote ng bata. Iniipon namin, pinaglalagyan namin ng tubig. So hindi namin siya sinasama sa basura. [We do not collect recyclable plastic because like Wilkins bottle which we use for children are collected and filled with water. Which is why we do not mix them with our wastes.]” (Gemma, 28, Office Worker).
The barangay’s lack of participation in FMCG initiatives is not only explained by the residents’ indifference or how they find these insensible for them to take part in. The reason for the non-involvement of some is just simply ignorance. These programs are not clearly communicated and circulated in the barangay, which is why not all are aware and participate. In fact, the barangay secretary disclosed that even if people are encouraged to participate in plastic recovery, they do not really put much effort to inform and persuade the community of these
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Lastly, there were plastic recovery programs before that convert plastic wastes into eco-bags. Residents were asked to participate by bringing plastic wastes to the program. The resident teacher hoped that they would continue these kinds of projects because it was useful for her when buying food in the marketplace.
“Matagal na pala yun e nangyari…yung naging ecobag yung mga plastic na tinatahi nila. Kasi meron pa akong ganyan na binigay nila…pero wala na matagal na yun…Pero maganda ibalik yun kasi maganda sa pamamalengke… kasi ano siya e hindi na siya mabubutas din, makapal na yun e parang mga denwood. Yung tulo ng pinamelengke mo na mga ano, at least nandun. Kaysa ang daming mong plastic bag, pag nabutas din wala din. Dagdag lang ang dumi at mahirap tunawin yun. [It happened long ago… they converted the plastic wastes to ecobag through sewing. I still have the bag given to me… but it was a long time ago… But its good if they bring the program back because the ecobag is useful when shopping... It does not get punctured; it is thick like denwood. The liquid coming from items you bought from the market do pass through the bag. Instead of having many plastic bags, which gets punctured easily. They add to pollution and are difficult to degrade.]” (Yasmin, 48, Teacher).
The importance and effectivity of these plastic recovery programs were also observed by one of the residents. She noticed the gradual decrease of the amount of wastes they had when she gave back plastic wastes to the companies.
Synthesis of Theory and Practice
Rousta (2018) claimed that studying the waste separation at its source is integral to understand the solid waste management, because contributing to the waste sorting system is essential to change waste into a value-added resource. Her claim was consistent with the EcoGov Project (2011) research which noted that one of the best practices is the full enforcement of proper waste segregation at its source. In this study, it was found that there is already a bottleneck at the source with some people not participating in waste separation.
Garbage is continued to be mixed after segregating wastes that can be bartered. These results were consistent with the call of previous studies of waste management in developing countries to create an efficient source separation system (Rousta, 2018). Rousta (2018) mentioned that generally, people have the wrong information on how to sort correctly, especially because knowledge is commonly transmitted through word of mouth via friends and family members. Similarly, in the study, the residents implied that segregation is a no-brainer, habitual (automatic) activity learned through common sense, but in fact, they are practicing incomplete and improper segregation, even based on the barangay’s ordinance on how to separate wastes. Hence, there is a lack of knowledge and information on sorting wastes in the barangay, as likewise reported by Rousta (2018).
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Although residents reported positive disposition towards waste separation, some still do not adhere to it. Rousta (2018) mentioned that factors to consider are “personal situations, convenience, task knowledge, opportunities and abilities [that] influence both behavior and attitude” (p. 24).
In the study, convenience was a great factor to consider among residents, may it be through having time, space, and enough facilities to perform waste separation. In Xu and colleagues’ (2017) research, they characterized these as elements of perceived behavioral control. Non- segregating residents of Barangay 852 shared that they fail to segregate because they are busy and have no nearby garbage bins to dispose of their trash. Such inconvenience may also explain why some residents employ a trash collector to have their wastes segregated and brought to the collection site every day. Another thing to consider is that each resident has their own lifestyle and situations that make waste separation impossible. Hence, how they perceived convenience is also affected by their subjective and personal circumstances (Rousta, 2018).
To further understand waste separation behavior, Rousta and Dahlen (2015, as cited in Rousta, 2018) identified three categorical factors: internal (attitude and intention), external (perceived behavioral control – knowledge, infrastructure, facilities, time, space) and socio- demographic factors (gender, age, income). Of these three, however, the last is unclear how it affects separation behavior (Rousta & Dahlen, 2015, as cited in Rousta 2018), while the other two have a similar foundation as the model proposed by Xu and colleagues (2017).
Due to the richness of qualitative responses, this research could further provide evidence for the Motivation-Opportunity-Ability-Behavior (MOAB) model by Olander and Thogersen (1995, as cited in Rousta, 2018). Motivation was greatly established in this research, while it could be assessed that what disconnects residents’ positive intention to segregate with behavior are their abilities (knowledge, habit, resources) and opportunities (overall situation). In summary, this study highlighted the following, which may explain why separating at its source is not being practiced:
1. Ability – Difficulty to change old habits and inability to form and sustain new desirable habits (discipline) 2. Ability – Limited knowledge and access to proper and complete waste segregation. 3. Opportunity – Lax implementation and monitoring of barangay waste management system and municipal waste collection; and 4. Opportunity – Delegation of waste separation responsibilities to other agents.
Information should be properly disseminated. Furthermore, the local solid waste management and collection in the barangay is not properly communicated, as exemplified by the conflicting perspectives that the residents shared. Rousta (2018) shared that for waste sorting and recycling behaviors to increase, “the design of information, types of information, types of communication channels, and the timing of dissemination are vital” (p. 24) and that first impressions of the waste management system can deeply influence waste sorting and recycling behavior among residents.
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Moreover, this study exemplified how past behavior can significantly affect habit formation and behavior (Xu et al., 2017). The residents’ “ningas cogon” mentality can be explained by how past behavior (non-separation of wastes) strongly dictates the residents’ current inaction to separate wastes. It seems to be difficult for them to change what they have already been accustomed to, and so even if they believe that waste separation is positive and contributes to the general welfare and health of the people and the environment, these attitudes are not enough to change their old habits, thereby, again, constituting an attitude-behavior gap.
Recommendations
Resource/Partnering with a FMCG Company. Another key learning is to partner up with an FMCG company proactively pushing for plastic waste management to gather more information on how programs were conceptualized. Through the partnership, the researchers may gain an understanding of the objectives of the program and cross-check with the participants’ experiences. It would also provide another perspective on the issued from the manufacturer side while reconciling how households perceive their program. Through this, it could elucidate a more detailed discussion on why a program is effective or ineffective. This may also attract more research participants due to sponsorship and brand awareness.
Expanding Scope of Study to City Government Level. This research was only able to tackle to the extent of the household and barangay level’s perspective on waste separation and waste management system. Therefore, it is recommended to examine the planned and implemented waste management policies, activities and programs initiated by the city government. Gaining perspective from contracted garbage collecting agents and city officials would carry out a deeper understanding of the interaction and responsibility of all levels (from household to barangay to city governments) and ultimately demonstrate the end-to-end process from waste collection, treatment and safe disposal as depicted in the waste management hierarchy framework.
Implement Action Research. In the future, Barangay 852 can implement the program in San Fernando, Pampanga where they hired residents as civil servants to collect food scraps and recyclables from every house daily and to pre-sort the recyclables before delivering it all to one of the 35 designated waste warehouses and be picked up by trucks (McDermott, 2017). This could work for a small community like 852, because scraps could be used as organic fertilizers as what Marikina does (Palafox, 2017), while recyclables could be exchanged for rice or cash equivalent (Visaya, 2019). In fact, this ongoing practice in Pampanga has also decreased their trash percentage to landfill by 68%. Waste warehouses usually perform further segregating, composting and recycling to prepare the wastes for transfer to disposal landfills or to long-term storages (Mateo, 2019). In effect, this could help residents to practice proper waste segregation while pushing them to be responsible and accountable for their wastes.
References
Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50, 179=211. Retrieved on November 02, 2018, from https://pdfs.semanticscholar.org/6256/ca4853f44ab9acb98f91f0d7848c54185ca7.pdf
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Albert, J. R., Gaspar, R., & Raymundo, M. (2015, July 08). Who are the middle class?. Rappler. Retrieved on October 07, 2018 from https://www.rappler.com/thought- leaders/98624-who-are-middle-class Deutsche Welle. (2017, October 06). The persistent plastic problem. Retrieved on October 03, 2018, from https://p.dw.com/p/2lO9Q EcoGov Project (2011). Good Practices in SWM: A Collection of LGU Experiences. Retrieved on July 14, 2019, from http://faspselib.denr.gov.ph/sites/default/files//Publication%20Files/ Good%20Practices%20in%20SWM%20- %20A%20Collection%20of%20LGU%20Experien ces.pdf Mateo, J. (2019). San Fernando fighting waste as well as mindsets. Philippine Star. Retrieved from https://www.philstar.com/headlines McAllister, J. (2015, May). Factors Influencing Solid-Waste Management in the Developing World. All Graduate Plan B and other Reports, 58. Retrieved on July 1, 2019, from https://digitalcommons.usu.edu/gradreports/528/ McDermott, A. (2017, September 14). This Philippine city is fighting ocean plastic with a clever solution to trash. Oceana. Retrieved on October 2, 2018 from https://oceana.org/blog Messenger, B. (2018, January 05). Interactive map - world’s most wasteful countries. Waste Management World. Retrieved on October 07, 2018 from https://waste-management-world.com Palafox, F. (2017, December 7). Ecological waste management. The Manila Times. Retrieved on October 14, 2018 from https://www.manilatimes.net/ecological-waste-management /367117/ Philippines (2000). Republic Act no. 9003: Ecological solid waste management of 2000. Metro Manila, Philippines: Congress of the Philippines, Republic of the Philippines. Posadas, D. (2014, May 22). Sachets help low-income communities but are a waste nightmare. The Guardian. Retrieved on October 02, 2018, from https://www.theguardian.com /sustainable-business/sachet-packaging-low-income-communities-waste-nightmare Rousta, K. (2018). Household Waste Sorting at the Source. (Thesis). Retrieved on July 1, 2019, from http://hb.diva-portal.org/smash/get/diva2:1148055/FULLTEXT01.pdf Senate Economic Planning Office [SEPO]. (2017, November). Philippine solid wastes at a glance. Retrieved on October 07, 2018 from https://www.senate.gov.ph The World Bank. (2018). Solid Waste Management. Retrieved on October 15, 2018 from http://www.worldbank.org Unilever (n.d). Waste & packaging. Retrieved on October 3, 2018, from https://www.unilever.com.ph/sustainable-living/the-unilever-sustainable-living- plan/waste-and-packaging/ Visaya, V. (2019, June 21). Cauayan City residents exchange plastic waste for rice. Philippine News Agency. Retrieved on July 1, 2019, from https://www.pna.gov.ph/articles Xu, L., Ling, M., Lu, Y., & Shen, M. (2017). Understanding Household Waste Separation Behaviour: Testing the Roles of Moral, Past Experience, and Perceived Policy Effectiveness within the Theory of Planned Behavior. Sustainability, 9, 625-651. DOI: 10.3390/su9040625
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COVID-19 Reflections Thoughts on Managing and Organizing in Times of Crises
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‘Diskarte’ in times of crises
Raymund B. Habaradas De La Salle University [email protected]
On the first day of the Metro-wide lockdown imposed by the government to contain the COVID-19 virus, I finished reading Christopher Hudson’s “The Killing Fields.” Based partly on the screenplay of the award-winning film with the same title, the book tells the story of New York Times’ journalist Sydney Schanberg and of his Cambodian assistant/interpreter Dith Pran at the time of the collapse of the Cambodian government in 1975, and the subsequent ordeal of Pran under the brutal Khmer Rouge regime.
After escaping execution by the Khmer Rouge by pretending that he was an uneducated man, Dith Pran had to work long hours in the open-pit mines of Dam Dek, east of Siem Reap. Like the other workers, he suffered from malnutrition, having to settle with his daily ration of 150 grams of rice in exchange for the backbreaking work of a slave. But unlike the others, Pran was resourceful. On the few square feet of land around his small hut in stilts at the far-end of the village, he grew tomatoes, tobacco and squash plants. However, the Khmer Rouge guards frowned upon this resourcefulness. Upon discovering Pran’s vegetable plot, they kicked his squash plants and uprooted his tomato plants, and told Pran, “It will no longer be necessary for the individual to supplement his diet! Angka will supply everything! In spite of his rage, Pran controlled his emotions. He knew that if he questioned authority, he dies.
It is uncanny how Pran’s experience under the Khmer Rouge mirrors what is now happening in our country. Proactive action and resourcefulness (or ‘diskarte’ as we say it in Filipino) seem to be frowned upon by the powers-that-be in this time of crisis. Illustrative is the case of Pasig Mayor Vico Sotto, who acted resolutely to deal with the challenges brought about by the epidemic.
He implemented a series of well-thought-out actions that endeared him not only among his constituents but also among netizens. He was quick in setting up a Rescue Emergency Disaster (RED) Training Center back on March 8 to prepare for the effects of COVID-19, and then proceeded with disinfecting public places, and with setting up community kitchens that prepared meals for those affected by the lockdown. Pasig also did immediate contact tracing and quarantine of those who had been in contact with COVID-19 patients.
After the Luzon-wide quarantine was announced, he pleaded with the national government to allow some tricycles to operate to serve as transportation for health workers, for staff assigned to perform essential services, and for emergencies. “Our risk assessment shows that we cannot completely ban tricycles,” he said, after determining the situation faced by his constituents. He added: “Sana makita po ng mga ginagalang nating lider—na may perspektibo kami sa LGU na maaaring di nakikita mula sa mas mataas.” What he got as a response was a rebuke from Malacañang, which said the national government calls the shots in a crisis, not the LGUs. President Duterte, in an apparent reference to Sotto, even threatened local officials with administrative and criminal charges if they do not strictly follow the lockdown guidelines. Now, wasn’t that an
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In “The Killing Fields,” Dith Pran wondered where the rice surpluses went, having once been to a communal storage depot and seeing enough rice there to feed the whole province of Siem Reap for a month. To him, it was a mystery that they were given so little to eat when there is so much that could be distributed to them. Again, the parallelism to what is happening now is uncanny.
One can’t help but wonder why it is the Office of the Vice President, with its small budget allocation, that is taking the lead in providing free transportation service and personal protective equipment (PPEs) to health workers in Metro Manila. Is it not fair to expect the Department of Transportation (DOTr) and the Department of Health (DOH), given their mandates and much bigger resources, to be at the forefront of these efforts instead?
Moreover, the Office of the President has vast powers and resources, including several billion pesos from the President’s discretionary and social funds—have these funds not been utilized for programs meant to address the COVID-19 crisis? Why is there still a shortage of testing kits for our people and of PPEs for our front liners? Why we haven’t seen more concrete action from the concerned government agencies is a mystery to me.
Given that the quarantine is now on its third week, the expectation is that the DOH should have already identified locations, and set up laboratories and testing facilities in addition to the Research Institute of Tropical Medicine (RITM) and the San Lazaro Hospital in Manila to rapidly augment testing capacity. DOH has yet to reveal its plan for this.
In the meantime, we were surprised by Marikina Mayor Marcelino Teodoro, who announced that the city government is ready to set up its own COVID-19 testing center. However, it could not proceed because the DOH disapproved the proposed center on the grounds that it does not meet strict biosafety standards. While we recognize the DOH’s ultimate authority in deciding matters of public health, one cannot help but be frustrated by what is happening. There is clearly something wrong when, in a time of crisis, proactive efforts by LGUs are dampened, and improvised solutions are discouraged, not only by a paralyzing bureaucracy but also by an insensitive national leadership.
The Khmer Rouge promised that “Angka will supply everything!” As a result, millions of Cambodians died under probably the bleakest chapter in its history. I hope that there will be no similar situation here in our country.
[Note: This piece first appeared on March 29, 2020 in manilastandard.net. Several weeks later, the Department of Transportation took over the free shuttle service for front liners that the Office of the Vice President operated for one month. Department of Health Secretary Duque praised Marikina City’s COVID testing center, saying it is “one of the best I’ve seen”; the Pasig City government allocated more than one billion pesos of its own funds to aid its residents not included in the list of beneficiaries of the Social Amelioration Program of the National Government; while the Inter-Agency Task Force for the Management of Emerging Infectious Diseases (IATF-EID) announced that it has adopted a “national-government-enabled, local government unit (LGU)-led, and people- centered” response to the COVID-19 pandemic.]
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The search for “good” leaders during COVID-19: Reflections on how value systems frame actions during a crisis
Eula Bianca Villar Asian Institute of Management [email protected]
It has been more than a month since the Philippine Government imposed the Enhanced Community Quarantine (ECQ) as a part of the efforts to decrease the exponential spread of COVID-19, and consequently keep the public health infrastructure from being overwhelmed. The experience of a pandemic is not necessarily new. Fatal pandemics that disrupt social systems at local, regional, and global levels have occurred before. Some of the examples that are relatable to COVID-19 include the 1918 Pandemic Flu (also known as the Spanish Flu) which resulted in an estimate of 50 million deaths worldwide,1 and the 1957 Influenza (also known as the Asian Flu) that developed from what was then described as a new influenza virus, H2N2, and resulted in an estimate of 1.1 million lives worldwide.2 However, there are certain contextual elements surrounding COVID-19 that make it “novel”, especially for leaders that are trying to address them.
First, there is no collective memory of a lived experience of a pandemic with this scale and magnitude in recent history. The rapid spread and virulence of COVID-19 far exceed those of its relatives SARs-CoV-1 and MERS-CoV, both of which also caused social disruption in recent history. SARS-CoV-1, which was first detected in 2003, affected approximately 8,437 people, and resulted in 813 deaths across the world.3 Meanwhile, MERS-CoV, which was first identified in 2012, affected about 27 countries worldwide, and caused an estimate of 858 deaths.4 Both SARS- CoV-1 and MERS-CoV have a high mortality rate (at 10 and 35 percent respectively), while COVID-19 has a reported mortality rate of only 3 percent.5 This has implications on the perception of “lightness” of COVID-19, which had consequences for the overall behavior of society. Many leaders did not immediately pay attention to the potential ripple effects that the outbreak could do to the health infrastructure, and many of them also resorted to language that downplayed, or at worst, denied the severity of impact of the virus.
Second, the tight interdependence of economies and the ease of movement across the world has accelerated the spread of this pandemic. Our current economic systems are embedded on the principle of connectedness and openness, and growth and prosperity models are inevitably grounded on these principles. Hence, calling for a solution that challenges the very principles of connectedness and openness, i.e. through physical distancing, travel bans, and closures of non- essential businesses, caused a dissonance among many leaders, which translated to an erroneously dichotomized choice between health and economic prosperity. As an example, some leaders decided too late to impose stricter measures on travel, citing the economic gains from tourism, while other leaders emphasized the importance of economic recovery by hastening the re-opening process of businesses.
While indeed COVID-19 is not unprecedented, the elements of newness described above are some of the factors why COVID-19 presents itself as a complex puzzle to address for our current leaders. This complexity is compounded by the criticality of time, criticality of life, high
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And yet, as grand a challenge as it may be, this is the time when we need our leaders the most, when we need, especially for the “good” leaders to show up and herald us through a way out of the crisis.
A “Good” Leader: What Is It?
Every crisis brings out the best or worst in a leader, and the varying ways in which leaders are managing the COVID-19 pandemic has triggered a discourse on what it really means to be a good leader, and which leaders can be considered exemplary in managing our way out of COVID- 19. There is an abundance of scientific literature regarding leadership in crisis contexts, including what to expect from a leader, and how to appropriately evaluate them. In 2013, crisis scholars Boin, Kuipers, and Overdijk published a scientific paper that proposed a comprehensive framework for evaluating crisis leadership. They argue that leaders who manage a crisis are often assessed on the surface level based on their symbolic performance. While this is an important measure, there are also other equally important tasks that crisis leaders are called to perform.
These tasks include: early recognition of a crisis, sense-making, making critical decisions, orchestrating vertical and horizontal cooperation, coupling and decoupling systems, meaning- making, communication, rendering accountability, and learning (Boin et al, 2013). Some of these tasks are performative in nature, and therefore require that leaders possess technical skillsets and a combination of specialist and generalist knowledge gained from formal and/or informal training. Meanwhile, other tasks, including sense-making and meaning-making, are also affective in nature, and require the ability of leaders to tap into their respective value systems.
Sense-making and meaning-making are critical moments in crisis management – these are the moments which could define the path towards action or inaction. Karl Weick, who has written seminal works on sense-making during crisis situations, coined the phrase cosmology episode in crisis contexts where individuals are all of a sudden confronted by a sudden loss of meaning due to the newness of the situation (Weick, 1993). Such loss of meaning trigger individuals to make sense of the situation in real time, as they resort to rationalization of certain actions.
This process of sense-making raises a very important question relevant to crisis leadership: what are the anchor points of individuals as they make sense [of a crisis]? How do they make sense, and what frames the “sense”, which in turn, frames the action (or inaction) of an individual?
Researchers in the area of cognitive decision-making established that in such moments of uncertainty (or using a Weickian language, in such cosmology episodes), individuals may resort to their belief systems (Gomez, 2019; Kahan, 2013; Kunda, 1990; Larson, 1994). Broadly, values are embedded in an individual’s belief system, and individuals have often used their values as anchor points when they make sense of a chaotic situation, which in turn orient their actions
85 | P a g e www.paomassociation.wordpress.com towards a certain direction. The thing about values, however, is that they are not consistent across individuals. Individuals develop values according to unique exposures. As human beings, leaders are molded differently by unique experiences, exposures, skillsets, and contexts. On that note, not all leaders respond the same, precisely because not all leaders are created equal.
There are a number of instances when we have seen values play out as anchor points for leaders to make sense of the current crisis, and consequently come up with an action. US President Donald Trump and Philippine President Rodrigo Duterte have been observed to be constantly using bravado and display of masculinity in their response to COVID-19, emphasizing the “strong man versus the pandemic” narrative.7 Values rooted in this “strongman” narrative may have translated to solutions that are militaristic and punitive in nature. For example, the crisis messaging of President Duterte has centered primarily around threats of violence for those who will not follow government orders of ECQ. Meanwhile President Trump started invoking war-time rhetoric, which is perceived by many as a dangerous metaphor during a pandemic when the importance of rigorous care is overshadowed by the appeal of heroic sacrifice and violence at all costs to defeat an invisible enemy.
Another set of values that surfaced as anchor points for certain leaders during this pandemic are scientific rigor and ethics. Germany’s Chancellor Angela Merkel, as well as Dr. Anthony Fauci who is a part of the White House Task Force on COVID-19 in the Trump Administration, have displayed consistent resort to science as their way of rationalizing what actions need to be undertaken. Chancellor Merkel is a scientist by training, while Dr. Fauci is a career scientist who has an extensive exposure to scientific rigor. Such values may explain why both Chancellor Merkel and Dr. Fauci are mindful of the precision of their messages and call to action, always resorting and reemphasizing the value of science in their respective strategies, and finally ensuring that the limitations of their call to action are communicated well – which, ultimately, is an exercise of ethics and accountability among scientists.
Care, empathy, and a grassroots-oriented decision-making are also very apparent in other leaders – including, among others, New Zealand Prime Minister Jacinda Ardern and Philippine Vice President Leni Robredo. Prime Minister Ardern’s crisis approach has a consistent message of inclusion, listening to her constituents and providing accessible platforms for them to communicate (e.g. use of Facebook live chats), and a consistent call to collaborative decision- making. Meanwhile, Vice President Robredo, whose service centers around assisting those at the margins (i.e. her rhetoric of “ang mga nasa laylayan”), and understanding the needs of the grassroots, seems to be using this as her anchor to approach the crisis. Note that since COVID-19 was officially announced as a global pandemic, the immediate resort of Vice President Robredo was to mobilize aid for those at the margins and the front-liners, acknowledging that these people are most exposed not just to the virus, but to the socio-economic inequities inherent in the current social system.
While the examples above are anecdotal, it opens up a discussion on the role of values as anchor points for leaders when they make sense of a crisis. How leaders make sense of a crisis is essentially a manifestation of how they rationalize a crisis, which in turn, orients them to a certain call to action. That is to say, a leader who is anchored on violence will use violence to address a crisis, a leader who is exposed to certain vulnerabilities and have a deep understanding of what it
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The search for a “good” leader during a crisis is, therefore, not only contingent on the efficacy of crisis response and the leader’s ability to perform the executive tasks expected of them, but also on their ability to anchor themselves on values, and use these values to herald their constituents out of a crisis. This is a contentious argument, as the definition of “good” leadership then becomes subjective. Not all values are positive, and certainly not all values are compatible with certain constituents. There is a degree of compatibility (between the leaders and the followers) necessary to also consider one crisis approach as “good” leadership.
Implications: The Uncomfortable but Necessary Discourse We Should Hold on “Good Leadership” during Crisis Situations
The reflections above give rise to uncomfortable questions, but necessary questions, nevertheless, on crisis leadership. While one cannot predict with precision what the future will look like, it is possible to imagine future scenarios from present signals. Such signals include grand challenges like systemic poverty, climate change, disasters arising from infrastructure and societal vulnerability, famine, gender inequality, economic crises, and epidemic, among other things that scale up at the global level (George, Howard-Grenville, Joshi, Tihanyi, 2016). COVID-19 is only one of the many grand challenges we are bound to face. Indeed, when many more of such challenges come in the future, it will be important to have leaders that constituents can collectively rely on for “good” leadership.
As such, we need to hold the necessary discourse on what good leadership means for us, and which leaders we elect to take us out of a crisis. Below are just a few points that we have to talk about:
First, values matter when choosing our leaders. If the future is going to look like a series of incremental crisis episodes, where humanity is faced with shock after shock, disruption after disruption, we have to make sure that we elect leaders whose values are compatible with ours. This means we, as constituents, also have to confront ourselves with the question of which values are our non-negotiables.
Second, values will be important when leaders inevitably have to bend the rules in order to make things work during a crisis. This is especially critical when the context is so new, and existing guidelines or templates for action are no longer applicable, due in part to scarcity of resources, incompatibility of organizational processes with the crisis, or a combination of both. In such instances, leaders may be forced to improvise from existing processes, and inadvertently bend the rules, or sacrifice existing processes, in order to preserve a bigger goal, e.g. preservation of life (Villar, 2018). When leaders have to resort to rule-bending actions, values may be the differentiating factor that can either make or break crisis management.
Third, while there is much emphasis on values, we must also be careful as to not commit virtue signaling. Competing values can lead to “better-than-thou” arguments and create a polarizing effect on the constituents. This can have dangerous and divisive effects on the
87 | P a g e www.paomassociation.wordpress.com constituents – which is also largely observed between those who support and those who do not support the approach of President Duterte. Much of the debate has been laden with virtue signaling on whose values are better. It is hard to manage this polarizing effect when we gauge leaders according to their values, but as emphasized above, while values are important, there are other factors to include when assessing the overall performance of a leader. Values are important, but they are not the end-all and be-all. As responsible individuals, it is important that we do not single out values and use it as a singular gauge for good leadership, but as a part of a bigger, holistic framework.
Fourth, it is important to remember that crisis leadership is not only exercised from the top, but also from the middle and base ranks – and wherever it is exercised, values will still matter. The self-organizing capacity of people who hold no formal positions of authority have exercised leadership in their own ways. This is especially seen among collective groups of individuals who were able to pivot their roles into to something that is relevant to the crisis, e.g. the fashion designers who pivoted to the creation of Personal Protective Equipment (PPEs) for the front-liners. The same is observed with farmers who have paired up with community kitchens to provide fresh produce and feed front-liners, low income families, and individuals at the margins (e.g. Cordillera farmers teaming up with Art Relief Mobile Kitchen).8 In a study that scopes out the innovation ecosystem in vulnerable spaces,9 the same phenomenon was observed among entrepreneurs who decided to pivot their services into social causes (e.g. PushKart.ph using their online grocery to deploy basic goods to victims of typhoon). These people are not mandated to act in a crisis, but the ability to pivot their roles into something that is relevant to a crisis may be a result of having anchored themselves on certain values such as service to the community.
Finally, understanding how values frame actions in crisis situations must also be complemented by discussions on where and how values are formed. From a total systems perspective, the formative years (and beyond) of future leaders matter. What they are taught, the realities they are exposed to, the skills, training, and reasoning they are taught will contribute to the development of their values. On that note, values formation at home, in school, in universities, and in the workplace will one day become an anchor point for how crises are managed. As educators and knowledge creators, we must be careful to not take for granted how we reinforce the values formation of our future leaders.
References
Boin, A., Kuipers, S., & Overdijk, W. (2013). Leadership in times of crisis: A framework for assessment. International Review of Public Administration, 18(1), 79-91. George, G., Howard-Grenville, J., Joshi, A., & Tihanyi, L. (2016). Understanding and tackling societal grand challenges through management research. Academy of Management Journal, 59(6), 1880-1895. Gomez, M. A. (2019). Past behavior and future judgements: seizing and freezing in response to cyber operations. Journal of Cybersecurity, 5(1), tyz012. Kahan, D. M. (2012). Ideology, motivated reasoning, and cognitive reflection: An experimental study. Judgment and Decision making, 8, 407-24. Kunda, Z. (1990). The case for motivated reasoning. Psychological bulletin, 108(3), 480. Larson, D. W. (1994). The role of belief systems and schemas in foreign policy decision-making.
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Political Psychology, 17-33. Villar, E. B. J. (2018). Architecting Purpose-Driven Improvisation towards Organizational Effectiveness in Extreme Environments: Case Narratives from Organizations during Typhoon Haiyan (Doctoral dissertation, Universitat Ramon Llull). Weick, K. E. (1993). The collapse of sensemaking in organizations: The Mann Gulch disaster. Administrative science quarterly, 628-652.
Acknowledgement
The author wishes to thank Miguel Alberto Gomez (Center for Security Studies - ETH Zurich) for his comments regarding belief systems and motivated reasoning among decision- makers, and Dr. Raymund Habaradas (RVR College of Business – De La Salle University) for his helpful feedback on the article as a whole.
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1 See description of 1918 Pandemic by Center for Disease Control and Prevention: https://www.cdc.gov/flu/pandemic-resources/1918-pandemic-h1n1.html 2 See description of the 1957 Pandemic by Center for Disease Control and Prevention: https://www.cdc.gov/flu/pandemic-resources/1957-1958-pandemic.html 3 Reported by World Health Organization as of 11 July 2003: https://www.who.int/csr/sars/country/2003_07_11/en/ 4 Reported by World Health Organization as of January 2020: http://www.emro.who.int/health-topics/mers- cov/mers-outbreaks.html 5 Reported by Swiss Federal Office of Public Health: https://www.bag.admin.ch/bag/en/home/krankheiten/ausbrueche-epidemien-pandemien/aktuelle-ausbrueche- epidemien/novel-cov/krankheit-symptome-behandlung-ursprung.html 6 See article by Scott Berinato, “The Discomfort You are Feeling is Grief”: https://hbr.org/2020/03/that-discomfort- youre-feeling-is-grief 7 See article by Sharmila Parmandand, “The Dangers of Masculinity Contests in a Time of Pandemic” https://oxfordpoliticalreview.com/2020/04/18/the-dangers-of-masculinity-contests-in-a-time-of- pandemic/?fbclid=IwAR0lELqeG6cL-ryi1QkUdhdT3FID-Yxr-21bB29xGthMVg1LfyJpKdGjOBQ 8 See article regarding collaboration between Cordillera Farmers and Art Relief Mobile Kitchen during the Taal Eruption: https://newsinfo.inquirer.net/1215601/crisis-kitchens-rise-as-taal-rumbles. Shortly after the community kitchen for Taal evacuees were deactivated (mission was completed), ARMK activated their community kitchens for those affected by the ECQ due to COVID-19. As of April 2020, there are five active kitchens in Luzon and Mindanao. 9 See TUKLAS Innovation Labs Study, “Exploring the Philippine Disaster Innovation Ecosystem”: https://drive.google.com/file/d/1af7NcnrG_LYx4znew_tC-Q5IUhmr08Km/view
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COVID-19: Lessons from a pandemic
Armando J. Aguado Mapúa University [email protected]
The novel coronavirus that has swept through the globe will long be considered as one of the largest disruptors the world has ever had. The crisis has caused unprecedented change globally, notable of which were the large-scale adjustments to people’s everyday lives. Working from home, a method that had been more the exception than the norm, suddenly became necessary overnight.
For years, companies have sought to harness technology in more effective ways in their operations. Digitization became a buzz word for many multinational companies, but it took on renewed importance when stringent quarantine measures took effect in various locations around the world.
Physical Distancing
We live in a highly digital world, but so much of our day to day lives has remained dependent on actual physical presence and contact. This ran completely contrary to one of the leading strategies of medical experts to beat the virus from circulating – the concept of physical distancing.
Physical distancing meant avoiding close contact with one another, limiting people’s movements, and not being in places where mass gatherings would occur. Working out of an office with colleagues? No longer allowed (with the exception of essential services). Attending classes at school? Definitely no longer allowed. Going to the mall to eat at a restaurant or watch a movie? Yes, you get the idea – also no longer allowed. And just like that, as one government after the other began implementing strict physical distancing measures, all these activities we had gotten used to doing came to an abrupt halt. But life couldn’t stop indefinitely, and when it became clear that things weren’t going to go back to “normal” anytime soon, people and businesses alike had no choice but to adapt.
Working from Home: The New Normal?
For companies that already had significant numbers of employees working flexibly, working from home wasn’t too much of an adjustment. But this was hardly the case for all, and in many industries, working from home was never even an option, either because it made no sense (e.g. retail establishments) or because the infrastructure just wasn’t there (e.g. offices who still predominantly use desktop computers, and therefore employees had no work-issued laptops). Other companies that were somewhat better prepared proceeded to implement their Business Continuity Plans (BCPs). Now a key component of any BCP is having the capability to continue key operations from multiple locations – the concept of redundancy. However, when country after country shut down all but essential businesses, even the best BCPs were tested.
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Take for example the shared services and business process outsourcing industries. Companies based in the US, Europe, and Australia who outsourced their customer service or support functions would tend to have operations in at least 2 separate countries outside of their home country, to ensure business continuity. However, when strict lockdowns were implemented in both the Philippines and India – two of the world’s largest countries for BPO and Shared Services work, the decrease in operational capacity was significant. While Operations teams were working out how to adjust to new government quarantine guidelines and get employees back in the office safely, similarly veined questions were emerging among the Human Resources groups of companies. Questions about which employees can be transitioned to work from home arrangements, how to continue tracking attendance and doing payroll while working remotely, or what to do with newly hired employees in the midst of an operational shutdown, all started cropping up.
Online Learning: Easier Said than Done
Outside the corporate environment, another industry that got hit badly was Education and Higher Learning. While some of the nation’s top universities had begun using online solutions (e.g. Canvas, Blackboard, Moodle, Sakai, etc.) for classes, it simply hadn’t reached the point of maturity yet. Even in universities with established online systems, classes were still predominantly held in the classroom, as has been the norm for decades.
When the quarantine resulted in long term class suspensions, universities that already had the infrastructure had little choice but to shift to conducting classes fully online, albeit to largely unfavorable feedback from students and faculty alike. There was simply no shortage of problems – poor Internet connections, faculty members who were simply uploading material without any discussion whatsoever, instructors who were not comfortable running online classes, students who had new quarantine-related responsibilities and couldn’t concentrate on their lessons, etc. The list went on and on. Because of the negative experience, many students had indicated that should online classes still be the norm in the next few months, they would rather not enroll first and just wait for face to face classes to resume. However, this whole experience has created a human resource problem rarely seen for the education sector – with potentially far reduced enrollment numbers, what would that mean for faculty members and non-teaching personnel, whose salaries are mainly derived from student tuition?
Looking Ahead
Having seen what has played out over the past few months, what can we do to make sure that we are better prepared, should this happen again?
Engage in Digital Transformation. Those long term, multi-year plans to go digital? As this pandemic will show, that just won’t work. Companies need to start thinking of digital transformation today. While working from home may still not be a feasible option for some (e.g. those working in restaurants, department stores, supermarkets, etc.), for many office-based employees, it can actually be possible. However, companies will need to be serious about exploring this option for the future. Yes, there will be capital investment required to potentially purchase new equipment, invest in the right software, and so on. But going digital is not just about preparing
91 | P a g e www.paomassociation.wordpress.com for another future pandemic – it can also lead to significant cost reduction and simplification for a business in the long term. By reviewing key processes and systems for opportunities to go digital, the overall net result is also optimization, often leading to financial savings that offset the investment cost in the transformation.
This does not just apply to the corporate environment either. While this may not hold true for all levels of education (e.g. primary school), secondary and tertiary level institutions can benefit from ramping up efforts to integrate online classes as part of their regular operations. As many universities can now testify, having the online infrastructure and using it to effectively hold classes are two very different things. While not much can be done about client-side factors such as a poor internet connection, a lot of the other issues that came up, such as faculty unfamiliarity with online tools, an aversion to online teaching, etc. can be remedied by ensuring its greater use during even times of normalcy. For schools that haven’t even invested in online delivery methods yet, this is a good time to reconsider the initiative and begin budgeting for it, as taking a proactive stance will only serve to benefit their preparedness efforts in the long term.
Ultimately, having a strong digital backbone across a company or institution’s operations is beneficial not just from a business continuity perspective, but also from a human resources standpoint – when employees and stakeholders can continue to do business virtually, people can stay employed and there is a higher likelihood of operations remaining online.
Build up Crisis Management and Business Continuity Planning. Most major companies will have crisis management and business continuity plans, but not all will adequately test and update them regularly. Good BCPs are living documents that contain detailed response plans to many potential scenarios, such as natural disasters, data corruption, cyberattacks, and yes – even severe illnesses and pandemics. Having one prepares the company to answer questions like:
• In the event of a BCP scenario, which roles can continue working flexibly? • How does company leadership reach out to, and check in, with the whole workforce? This includes urgent communications, advisories, etc. • Are there clear prevention measures in place – and teams assigned that can step up to implement these measures – in the event of a crisis? • What is the command and control structure in place if something happens?
In the wake of COVID-19, many companies have had to come up with solutions to respond to the shutdown and support employees on the fly – some by offering financial support to their personnel affected by the stoppage in operations, some by subscribing employees to telehealth and online medical consultation services, others by providing paid pandemic leave in case the employee (or a family member) was infected by the virus. In many cases, there was a scramble to transition employees to work from home arrangements and identify and protect critical sites required to maintain operations, all while remaining open to serve clients and the general public.
To reduce the need for improvisation, continuity plans can be worked out ahead of time, with management testing how these can be implemented and deployed at a local, regional, and global level without too many approval touchpoints and unnecessary delays. Especially for multinational companies, ensuring that local teams are empowered to make decisions on the
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PHILIPPINE ACADEMY OF MANAGEMENT E-JOURNAL VOL. 3 NO. 1 ground, while coordinating with global leadership, will help to ensure that response plans are applicable locally but still remain in sync centrally. Even smaller companies that may not see a need to have a comprehensive BCP in place can benefit from having a basic crisis management plan. This plan would answer at the very least the important questions, like in the event of another interruption to the company’s business as usual practices, what steps need to be taken? Do employees know what they need to do, even for the most basic disruption scenarios? Having a clear plan to answer these questions is the first step to having a coherent response in times of a crisis.
At some point, the spread of the virus will be largely contained, with quarantines and travel restrictions lifted, and establishments slowly reopened. The Black Swan theory, popularized in the world of finance, talks about extremely rare events that are unpredictable, have widespread effects and consequences, and after its occurrence, leaves people with the general belief that the event could have actually been anticipated to happen. The COVID-19 pandemic has become the Black Swan event for many companies in 2020, but if history is to be the judge, it will not be the last unpredictable major event to hit businesses and organizations in the years to come. Being prepared for the next one is not a luxury; it is a necessity. Even after the semblance of “normal” has been restored, the lessons from this pandemic must never be forgotten.
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Author Guidelines
Manuscript requirements
1. Novelty: The contributions should be original and unpublished. They must also currently be not under consideration in any other journal. 2. Number of pages and layout a. Maximum of 20 pages (8.5” x 11” paper), inclusive of tables, figures, references, and appendices b. Typeface and font size: Times New Roman 12 points c. Text spacing: Single, with one space allotted in between sections d. Manuscript title: font size 14 points, boldface e. Section headings (Introduction, Methods, Results/Findings, etc.) are in boldface, sub-headings in italics f. Margins: 1” on all sides g. Pagination: top right 3. Manuscript format a. Research articles should include the following common sections: Title, Abstract, Keywords, Introduction, Methods, Results/Findings, Discussion, Conclusion, Recommendations (if any), Acknowledgments (if any), and References. b. Five to seven keywords must be indicated. c. Tables and figures should be inserted within the text itself instead of being appended to the manuscript. d. The names and all other details of the authors should not be indicated anywhere in the manuscript (i.e. institutional affiliation, contact number, etc.). These should appear only on the Cover Page. e. The text must only be written in a single column. Final formatting will be done by the editors. 4. Cover page a. The manuscript comes with a Submission Form. This is not included in the pagination of the manuscript, and it comes as a separate document when sent via email. b. If there are multiple authors, the names should be arranged according to the extent of their research contribution. If all the authors had more or less equal contribution, the names must be arranged alphabetically. 5. Reference guide a. The e-Journal makes use of the APA Formatting and Style. Contributors must utilize this format consistently throughout their manuscript. b. For electronic references, provide the DOI (digital object identifier). If this is not available, provide the complete URL that leads to the actual online document, including the date of access. Likewise, indicate all information pertaining to the article (e.g., author, title of article, date of publication).
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6. Copyrighted materials and acknowledgments a. Copyrighted materials (data, table, illustration, photograph, etc.) that are included in the manuscripts must have been cleared first from the copyright owners prior to submission to the Journal. b. Copyright owners must also be mentioned in the Acknowledgment section. For tables, figures, or photographs reproduced from other sources, authors must acknowledge the source in the caption identifying these.
Submissions, acknowledgments, and communications 1. All submissions should be sent through email. Two electronic copies should be submitted: one in PDF format then the other in MS Word format. Emails should be sent directly to [email protected] and [email protected] with the subject heading “PAoM e-Journal: Manuscript Submission”. 2. For manuscripts with several authors, the authors should assign a Corresponding Author to whom communications shall be sent. The corresponding author will be responsible for informing his/her co-authors about the status of their submission. 3. Submissions shall be acknowledged in writing by the Managing Editor or his designated staff. If no such acknowledgment is received by the Corresponding Author within one week, follow up should be done with the Journal.
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The Contributors
Armando J. Aguado Mapúa University [email protected]
Armando J. Aguado is an affiliate of the American Psychological Association, an HR career professional, and a lecturer with the Department of Psychology of Mapúa University. He earned his Doctor of Business Administration and Master’s in Industrial / Organizational Psychology degrees from De La Salle University.
Soleil G. Baria De La Salle University [email protected]
Soleil G. Baria has a master’s degree in financial engineering from De La Salle University. She is an Associate Subject Matter Expert in Enterprise Risk Management for a Property & Casualty Insurer and takes part in research topics on Insurance and Risk Modelling.
Angelique C. Blasa-Cheng De La Salle University [email protected]
Angelique C. Blasa-Cheng is an assistant professor in the Management and Organization Department of De La Salle University (DLSU) and teaches Management and Organization and Corporate Social Responsibility courses. She graduated with a degree in B.S. in Chemical Engineering in DLSU and took her Master’s in Business Administration in the same university. She is currently taking up Doctor of Philosophy in Business. Her research interests include sustainability and environmental protection.
Minchu R. Decena University of San Carlos [email protected]
Minchu R. Decena is an Associate Fellow in People Management of the Philippine Society of Fellows of People Management (PSOF) and is presently the Vice President of the Human Resource Division at the Chong Hua Hospital. She holds an Executive Master in Business Administration and a Bachelor of Science in Psychology degrees. She is currently a Ph.D. Business Administration student at the University of San Carlos. Her research interests are focused on organizational development, human resource strategy, and employee relations.
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Aristotle Manuel D. Go Palawan State University [email protected]
Aristotle Manuel D. Go is a faculty member at the Department of Accountancy in Palawan State University. He is currently pursuing PhD Business in De La Salle University. Prior to his doctoral studies, he served as President of Philippine Institute of Certified Public Accountants (PICPA) – Palawan Chapter. He also served as Treasurer of PICPA – Southern Tagalog Region and National Association of Certified Public Accountants in Education (nACPAE). His research interests include financial inclusion, base-of-the-pyramid innovation, and mobile payments.
Ranzelle T. Go De La Salle University [email protected]
Ranzelle T. Go graduated with the degree in A.B. Communication Arts and B.S. Applied Corporate Management from De La Salle University. She is currently employed as Infrastructure Analyst in a banking company.
Raymund B. Habaradas De La Salle University [email protected]
Raymund B. Habaradas is a Full Professor at the Management and Organization Department of the Ramon V. del Rosario College of Business of De La Salle University and is the holder of the Ambassador Ramon V. del Rosario Chair of Entrepreneurship. He does research on corporate social initiatives, social entrepreneurship, and SME development. He is a Fellow of the Social Enterprise Research Network (SERN) of De La Salle University, and former President of the Philippine Academy of Management.
Jana D. Josef De La Salle University [email protected]
Jana D. Josef graduated from De La Salle University with the degree in B.S. Applied Corporate Management. She is currently working as a Marketing Solutions Analyst for an e-commerce company.
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Ian Benedict R. Mia Philippine Academy of Management e-Journal [email protected]
Ian Benedict R. Mia is an editorial assistant and webmaster of the Philippine Academy of Management e-Journal. He is also a freelance academic researcher with previous works mainly on social entrepreneurship. He graduated from De La Salle University with a double degree on psychology and business management, respectively. His research interests include social entrepreneurship and sustainability management.
Fabienne V. Panelo De La Salle University [email protected]
Fabienne Renee V. Panelo graduated from De La Salle University with a bachelor’s degree in Psychology and Applied Corporate Management. She held internships in Marketing, Human Resources and Supply Chain with multinational companies. She intends to engage in work that focus on developing her creativity, strategic thinking and management skills.
Lauro Cipriano R. Silapan, Jr. University of San Carlos [email protected]
Lauro Cipriano R. Silapan, Jr. is an Assistant Professor of the Business Administration Department of the School of Business and Economics of University of San Carlos, Cebu City, Philippines. Currently, he is the Assistant Dean of the School of Business and Economics. He finished his DBA from De La Salle University, Manila. His research interests are in the fields of entrepreneurship, business and management, CSR, social entrepreneurship, and innovation.
Tomas S. Tiu De La Salle University [email protected]
Tomas S. Tiu is a faculty member at the Financial Management Department of the Ramon V. Del Rosario College of Business of De La Salle University. He has a Ph.D. Commerce from the University of Santo Tomas. His research interests are in finance, derivatives, health care policy, banking, and risk management.
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Eula Bianca Villar Asian Institute of Management [email protected]
Eula Bianca Villar is an adjunct professor at the Asian Institute of Management. She holds a PhD (Cum Laude) from La Salle - Universitat Ramon Llull University in Barcelona, Spain through the European Union Marie Curie Fellowship. She has taught at the graduate and undergraduate levels in De La Salle University - College of Business, Silliman University - School of Public Affairs and Governance, and La Salle - Department of Business and Technology. She has worked with international NGOs and small businesses as a research consultant on how organizations navigate disaster environments, and how to foster innovation and resilience in crisis contexts. She has also authored academic and non-academic articles on organizing processes in disaster contexts, organizational resilience, sustainability, and disaster management.
Note: Mr. Vincent Anthony V. Uy is a co-author of the manuscript titled “Trash Talks: A Phenomenological Study on the Waste Separation Behavior and Awareness on FMCG’s Plastic Recovery Initiatives of Barangay 852, Pandacan, Manila”. He is a graduate of De La Salle University with a degree in Bachelor of Science in Applied Corporate Management.
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